|
語言、語言學、和語言基礎論 -- 開欄文
|
瀏覽8,255 ｜回應20｜推薦1 |
|
|
|
語言的重要性不需我強調。到目前為止，人們對語言的起源和演化所知不多。語言對人心理與思考的影響更是讓科學家摸不著頭腦。本城市過去也刊登了一些這方面的研究報告。本欄先轉登兩篇相關文章。
第一篇討論關於語言起源以及使用語言所必須具有的先決條件(請見本欄第二篇文章)；它們包括身體結構和大腦功能等等面向。
今年是微軟「書寫軟體」發行40周年紀念。第二篇討論微軟「書寫軟體」對一般人在使用語言上的微妙影響(請見本欄第三篇文章)。此文和《網際網路的起源和演化》參看，我們可以體會到技術做為文化的一部分，它是如何在不知不覺中影響著人類的生活。
我計畫抽空整合本城市討論/報導過的各個重要議題；第一步是把相關文章的標題附上超連結合輯起來，以便搜尋。第二步則是把我對它們的觀點做系統性的陳述。
本文於 修改第 7 次
|
|
奧斯汀「言談行動論」術語試譯
|
|
|
推薦1 |
|
|
|
本欄上一篇貼文作者奧提斯先生應該是位哲學的專業研究者；他對(奧斯汀)「言談行動論」的介紹簡明扼要，掌握到重點。對語言或語言應用有興趣的朋友，值得花時間一讀。
該文各段字數冗長，讀起來吃力；我根據「一段一個主題」原則，把它們個別再分成幾個小段落；此外，補增了各節序號以便指涉。
我大概是80 -- 90之際，接觸到奧斯汀的「言談行動論」。如該文所述：奧斯汀這個理論在學術界的影響和應用極其廣泛(1)。它對我有相當大的啟發；我對人際溝通和社會事務的了解；討論相關議題的論述基礎；以及自己行文文風格等方面，都有該理論的影子。
此處就該文第3節標題所提到「言談行動論」的三個基本術語，以及三者的總稱，依序提出我的翻譯和解讀；請指教(該文第2.3節)：
1) 「一般性言談(行為)」：一般性的發言或交談行為(敘述或描述)。
2) 「動作導向性言談(行為)」：和我們的發言字面上相當(等同)的發言或交談行為。
3) 「結果導向性言談(行為)」：我們企圖達到一個特定結果/效果的發言。
4) 「動作言談」；它是奧斯汀統稱以上三個基本術語的用詞。”performative” 在這裏並不是「表演」或「履行」的意思；奧斯汀取其「做事」或「行動」義；用它來汎指「產生影響或結果」的「發言」，或因這些「發言」所引發的「行動」。他的目的是：區隔上三類「敘述性」發言和「敘述性」(「描述性」) 「發言」(或文字「論述」)。在「動作言談」(大「動作」)外，也可以譯為「言談行動」(心動不如「行動」)。此詞有學者以 “performative act” 表達，以求一致。”act” 在此特指 ”discursive act”，而非泛指各式各樣的「行為」/「動作」。
附註：
1. 關於該理論在日常生活中的應用，請參見本欄2025/10/27貼文：《語言做為操縱/控制的工具》(作者：The Female Code)。
本文於 修改第 3 次
|
|
奧斯汀「言談行動論」簡介 -- Outis
|
|
|
推薦1 |
|
|
|
Speech Acts — How to Do Things with Words
The Theory of Performative Utterances
Outis, 05/28/26
1. Distinction between constative and performative utterances
J. L. Austin’s How to Do Things with Words, based on the William James Lectures delivered at Harvard University in 1955 and published posthumously in 1962, revolutionized the philosophy of language by challenging the traditional assumption that the primary function of language is to describe states of affairs or convey propositions that are either true or false.
Austin begins by drawing a distinction between constative utterances, which are statements that can be evaluated as true or false, such as “The cat is on the mat,” and performative utterances, which do not describe but perform an action in the very act of being uttered.
Classic examples of performatives include “I do” in a marriage ceremony, “I name this ship Queen Elizabeth,” or “I bet you sixpence it will rain tomorrow.” These utterances are not true or false in the constative sense; instead, they succeed or fail depending on whether the action is properly carried out.
This initial contrast highlights Austin’s insight that language is not merely descriptive but can itself constitute actions. However, as the lectures progress, Austin demonstrates that the distinction is not as sharp as it first appears. Many constative utterances also perform actions, and performatives can involve descriptive elements.
The apparent binary ultimately gives way to a more nuanced general theory of speech acts, showing that saying something is often a way of doing something. This shift underscores the limitations of truth-conditional approaches that dominated earlier philosophy of language and emphasizes the performative dimension present in all linguistic activity.
2. The felicity conditions: uptake, sincerity, and conventional procedures
For performative utterances to succeed, Austin introduces the concept of felicity conditions, which replace the truth-falsity evaluation applied to constatives. These conditions ensure that the performative is “happy” or felicitous rather than “unhappy” or infelicitous.
Key among them are the existence of a conventional procedure with a conventional effect, the appropriateness of persons and circumstances, the correct and complete execution of the procedure, and the presence of requisite thoughts, feelings, or intentions. If these are violated, the act may “misfire” (resulting in no act being performed) or be an “abuse” (where the act occurs but insincerely).
Uptake refers to the audience’s understanding and acceptance of the illocutionary force of the utterance, which is essential for the act to take effect.
Sincerity conditions require that the speaker genuinely holds the relevant intentions or beliefs, such as actually intending to fulfill a promise.
Conventional procedures tie speech acts to social institutions and shared practices, explaining why not anyone can perform any act in any context — for instance, only an authorized person can pronounce a couple married. Austin’s detailed exploration of infelicities, including misinvocations, misexecutions, and abuses, provides a rich framework for analyzing how speech acts can go wrong in practice.
3. Locutionary, illocutionary, and perlocutionary acts
As Austin refines his theory, he replaces the constative-performative distinction with a tripartite analysis of speech acts.
The locutionary act involves producing sounds or marks that conform to vocabulary and grammar, essentially the act of saying something with a certain sense and reference.
The illocutionary act is what is performed in saying something, such as asserting, promising, ordering, or warning; it carries the conventional force of the utterance.
The perlocutionary act is what is achieved by saying something, the consequential effects on the audience, such as persuading, frightening, or amusing them.
This framework allows for a more comprehensive understanding of linguistic action. For example, uttering “I promise to come” involves a locutionary act (producing the meaningful sentence), an illocutionary act (promising), and potentially various perlocutionary effects (reassuring the hearer or creating an obligation).
Austin stresses that illocutionary acts depend on conventions and uptake, while perlocutionary acts are more contingent on actual consequences. This distinction has proven foundational for subsequent developments in pragmatics.
4. Development from “performative utterances” to a general theory of speech acts
Austin’s lectures trace an intellectual evolution from the initial focus on explicit performative verbs to a generalized theory applicable to all utterances. Early emphasis on overt performatives like “I apologize” or “I declare” expands as he recognizes that many acts can be performed without explicit verbs, through implicit or indirect means.
The realization that even constative statements have illocutionary force — such as asserting or informing — leads to the conclusion that the performative dimension is pervasive. Austin explores classifications of illocutionary acts into families like verdictives, exercitives, commissives, behabitives, and expositives, though he presents these as tentative.
This development reflects Austin’s ordinary language method: patient examination of examples, attention to nuances, and avoidance of overly rigid systematization. By the end, the theory encompasses how all speech is action within social contexts, paving the way for more formalized accounts while retaining sensitivity to ordinary usage.
5. Critique of truth-conditional semantics (focus on use)
A driving motivation behind How to Do Things with Words is Austin’s critique of truth-conditional semantics, which reduces meaning to the conditions under which sentences are true or false. Austin argues that this focus, inherited from logical positivism and earlier analytic traditions, neglects the myriad ways language functions in practical life.
By prioritizing use over abstract truth conditions, he shifts attention to how speakers deploy utterances to achieve social and practical ends. Many utterances cannot be meaningfully evaluated as true or false but must be assessed by felicity or effectiveness.
This use-oriented approach aligns with ordinary language philosophy’s emphasis on context, conventions, and actual practices. It critiques the philosopher’s tendency to overgeneralize from descriptive statements, showing instead that language is a tool for action embedded in forms of life. Austin’s focus on use anticipates later pragmatic turns and underscores that meaning is not exhausted by propositional content alone.
6. Influence on Searle, Grice, and modern pragmatics
Austin’s theory profoundly influenced John Searle, his student, who systematized and extended it in Speech Acts (1969) by
providing explicit rules for illocutionary acts,
refining felicity conditions into preparatory, sincerity, and essential conditions, and
offering a taxonomy of five basic illocutionary types: assertives, directives, commissives, expressives, and declarations.
Paul Grice complemented this with his theory of conversational implicature and the Cooperative Principle, addressing how speakers convey more than literal meaning through context and maxims.
Together, Austin, Searle, and Grice laid the foundations for modern pragmatics as a field studying language in use.
Their combined influence moved philosophy of language toward context-sensitivity, speaker intentions, and communicative intentions, shaping developments in relevance theory, discourse analysis, and experimental pragmatics. While Searle formalized Austin’s insights, Grice added inferential layers, creating a robust toolkit for analyzing indirect speech acts and non-literal communication.
7. Applications in linguistics, law, and social philosophy
Speech act theory has found wide applications across disciplines.
In linguistics, it underpins pragmatics, informing studies of politeness, indirectness, cross-cultural communication, and second-language acquisition.
In law, it illuminates how legal utterances like contracts, verdicts, and statutes perform binding actions, with felicity conditions relating to authority, procedures, and intent central to legal interpretation and validity.
In social philosophy, Austin’s ideas inform analyses of power, identity, and social reality construction, influencing thinkers like Judith Butler on performativity in gender and Pierre Bourdieu on linguistic markets and symbolic power.
The theory also extends to ethics, political philosophy, and artificial intelligence, where modeling communicative intentions is crucial for dialogue systems. Its emphasis on conventions and uptake highlights how language both reflects and shapes social institutions and power relations.
Further Readings
* Austin, J.L. How to Do Things with Words (2nd ed., eds. J.O. Urmson and Marina Sbisà, Harvard University Press, 1975) — the William James Lectures.
* Austin, J.L. Philosophical Papers (3rd ed., eds. J.O. Urmson and G.J. Warnock, Oxford University Press, 1979) — contains earlier papers on performatives.
* Searle, John R. Speech Acts: An Essay in the Philosophy of Language (Cambridge University Press, 1969) — systematic development of Austin’s theory.
* Gustafsson, Martin & Sørli, Richard (eds.). The Philosophy of J.L. Austin (Oxford University Press, 2011) — essays on speech acts.
* Levinson, Stephen C. Pragmatics (Cambridge University Press, 1983) — Austin’s influence on pragmatics.
* Sbisà, Marina & Turner, Ken (eds.). Pragmatics of Speech Actions (De Gruyter, 2013).
* Green, Mitchell. “Speech Acts,” Stanford Encyclopedia of Philosophy.
* Additional resources: Hornsby, Jennifer and Longworth, Guy on Austin’s legacy; works on indirect speech acts and applications in legal theory and feminist philosophy.
Written by Outis
Published in LICENTIA POETICA
Unveiling the Soul of Expression. Delve into profound exploration of liberated discourse. Explore the interplay of emotions and ideas, as this publication navigates the intricate realms of philosophy.
本文於 修改第 1 次
|
|
人工智能真有「思考」能力？ - Matt Fujimoto
|
|
|
推薦2 |
|
|
|
下文第1節所舉「比喻」論點以及第2、3兩節的論述，近於我討論過多次的「擬人化謬誤」。
下文的標題看起來是關於「人工智能」，但它的主題其實是：「語言的運用」；故置於此欄。
參考文章和書籍：
* ”Metaphors We Live By” (George Lakoff/Mark Johnson)
* AI may never think like us… and that could be good news
* Words, words, words
以上第2篇文章在5,000字以上，第3篇文章近4,000字；我目前沒有腦力讀它們。附錄於此，有興趣者不妨一試。
AI Is Not Thinking. We Just Say It Is
Why the words we use to talk about AI matter
Matt Fujimoto, 06/16/26
0. 前言
If you are like me, you use AI almost every day. Whether it is for my research or as my default search engine, AI has become a part of my daily life. One of the stranger parts of using it now is that you can choose whether you want the “thinking” model or not.
But I’ll be honest with you. I do not know what the difference is.
I know a “thinking” model is supposed to be better at more complex questions and take longer to produce an answer than a “regular” model. In that sense, the label is useful. I know what button to click when I want help with something complicated. Yet the label still confuses me.
As a philosopher, the idea of calling what AI does ‘thinking’ naturally raises a lot of questions outside of practice. People ask whether AI is conscious or can think for itself. In fact, there has been an explosion in the discourse around AI in this regard.
The problem is that we may already have been primed to answer a certain way. Discussions around AI often use words like ‘thinking’, ‘hallucinating’, or ‘learning’. Thus, when we are asked if AI knows what it is doing or if it is conscious, then we often point back to these words as proof.
Here, I want to argue that we do not believe AI is thinking because we discovered or created a mind. We believe it because the use of thinking language around AI has trained us to see one there when in fact AI is not thinking — at least, not in the ordinary human sense of the word.
I believe what has happened instead is that a useful metaphor hardened into a literal meaning. In other words, what began by saying AI acts as if it thinks because it helped us understand a complicated technology turned into the fact that AI thinks, with the words “as if” simply being dropped.
This move, accidental or not, has deep-reaching implications and is behind many confused ideas regarding technology. Once we call AI a thinker, other ideas quickly follow. If AI thinks, maybe it understands. If it understands, maybe it has agency. And if it has agency, maybe it has consciousness.
1. The Metaphors That Made Computers Friendly
Computers have always relied heavily on metaphoric language. We have desktops, folders, clouds, and trash all because they help put highly technical concepts into terms all of us can quickly grasp. These metaphors worked because they made something unfamiliar feel familiar. They allowed ordinary people to use complicated machines without needing to understand code, circuits, or pathway allocation.
Take the ‘cloud,’ for example. Your photos are not sitting in the sky. They are stored in data centers, on servers, using cables, electricity, cooling systems, and physical infrastructure. The term ‘cloud,’ on the other hand, is easier to understand and easier to sell as a product to users. I may not understand the computer science behind how cloud storage makes sure I don’t lose important documents or pictures of my daughter. But I can understand how the ‘cloud’ allows me to retrieve pictures even if they have been deleted from my phone.
In fact, a lot of teaching and explaining revolves around the use of comparison to connect something not understood to something that is. As a teacher, I regularly compare learning a language to going to the gym. Building physical muscle is easier for students to wrap their heads around than something abstract like language ability. Comparing the two helps them see that what I am asking them to do is like telling them to go to the gym four days a week.
With AI, the metaphors are a special case because they borrow from mental life. “Thinking,” “learning,” “reasoning,” “understanding,” and “hallucinating” are not just interface metaphors. They are person-words in that these words are used only to describe the actions of people and nothing else — until recently.
2. When “As If” Disappears
The most important word in all of this is probably “thinking.” Other AI words matter, but thinking is the gateway. Once we accept it, much of the rest follows. Thinking is not just one mental activity among others. It is the word we use for the inner life that seems to stand behind all other mental activity such as reasoning, understanding, judgment, and intention.
This is why the word is so tempting. AI often does things that look like thinking from the outside. It answers difficult questions, summarizes complex documents, writes code, explains mistakes, and solves problems in steps. All things we humans have been doing since before computers.
OpenAI’s o1 announcement, for example, described a model that was trained “how to think productively” and said its performance improved with more “time spent thinking.” It also compared the process to “how a human may think for a long time before responding to a difficult question.”
This language was used in order to make the world of tokens, weights, inference, reinforcement learning, and probability easy to understand. Furthermore, no one wants to give a university computer science lecture every time they have to describe what a chatbot is doing. “Thinking” is shorter. It gives the user a practical sense of what kind of tool they are using.
But this shortcut has consequences.
At first, “thinking” may be understood as shorthand. The model is not literally thinking, but it is doing something like thinking that the comparison helps. This is mainly the case because the system was built to replicate the output of the human mind. The problem begins when the shorthand becomes the concept itself. The longer phrase “As if thinking” becomes simply “thinking.”
This is a kind of linguistic priming.
If I am told a system is calculating, I see calculation. If I am told it is generating, I see generation. If I am told it is thinking, I begin to look for thought. Because AI is designed to produce human-like language, the evidence is easy to find. The flow of electricity through circuits becomes a mental life in reality, not just metaphor. Yet, the system has not changed just the description. And once the description changes, so does what we think we are seeing. It is as if we are being led by the nose to the answer and forgetting that fact.
Of course, someone might object that this depends on how we define thinking. If thinking simply means solving problems, manipulating symbols, generating useful outputs, or moving through steps toward an answer, then perhaps AI does think by such a definition.
However, that is not usually what people mean when they ask whether AI can think. They are not asking whether a system can produce an answer. They are asking whether there is something mind-like behind the answer. They are asking whether the performance points to understanding, intention, judgment, or experience.
3. The Philosophical Consequence of Grammar
This tendency to codify linguistic shorthand or mistakes is not limited to technology. Wittgenstein famously warned that many philosophical problems arise when language “goes on holiday.” In other words, many confusions begin when words are taken away from their ordinary use and made to do strange work elsewhere. We then treat the confusion created by language as if it were a discovery about reality.
Let’s use AI as an example.
The word “thinking” has its ordinary home in human life. Human thinking is not just output. It is connected to bodies, experience, memory, desire, responsibility, fear, hope, confusion, and the strange feeling of being someone in the world. When I say that I am thinking, I do not mean only that words are being produced or my neurons are firing. I mean that I am trying to understand something from within a life that is mine.
Thinking ‘goes on holiday’ when I take the sentence “I am thinking” and, through the rules of grammar, change the subject of the sentence to something like “X is thinking” where X can be anything that grammatically fits.
There are obvious cases where such an artificial sentence clearly fails, such as “the chair is thinking,” in that I am not going to mistake that for a true sentence. Yet in borderline cases the question becomes harder to answer. Just take sentences such as “the dog is thinking” or now “AI is thinking”.
AI, unlike chairs, presents to us some of the outward signs of thinking that we see in humans. Sometimes it imitates them very well, and without internal access we feel that, at least metaphorically, it is ok to utter the sentence “AI is thinking.” At the very least, such a sentence is comprehensible.
The mistake is that we take this case of anthropomorphism, this case of a linguistic grammar mistake, and attribute to it a technological and philosophical. Again, the issue is not the metaphoric language. Humans anthropomorphize everything. We yell at our cars, name our Roombas, and accuse our phones of acting weird. The mistake is treating anthropomorphic language as evidence of reality.
4. Why the Words Matter
At this point, someone might say this is just semantics. Maybe AI does not think in the human sense, but who cares? If the tool works, why worry so much about the word?
The answer is that usefulness is not the same as truth. A metaphor can be useful, clarifying, and even necessary while being false if taken literally. Calling online storage “the cloud” helps people understand a technical system, but no one concludes that their family photos are floating above them in the sky. The metaphor works because we know where it stops.
The trouble with AI language is that the stopping point is much less obvious. When we say that a model is “thinking,” “learning,” or “understanding,” we are borrowing from ourselves. We are using words that normally belong to minded, embodied, responsible beings and applying them to systems that produce human-like language without living a human life.
That does not make the metaphor useless. In many ordinary contexts, it works well enough. If I ask whether a model “understood” my prompt, I usually mean whether it responded in a relevant way. If I choose the “thinking” model, I usually mean that I want a slower and more careful answer. In everyday use, these shortcuts are convenient. They help us navigate the tool.
But the fact that a phrase is useful does not mean it is innocent. The danger comes when we forget that we are using a shortcut at all. “AI thinks” begins as a convenient way of describing a pattern of behavior, but it can quietly become a claim about what the system is. The grammar stays the same, while the meaning hardens. What began as metaphor starts to look like discovery.
This is where we risk tripping over our own language.
We ask whether AI has understanding, agency, or consciousness, but part of the answer may have already been smuggled into the question by the words we chose. If we describe a system as thinking for long enough, then asking whether it really thinks starts to feel natural, even inevitable. But perhaps that feeling tells us less about the machine than it does about the language we have allowed to surround it.
So the point is not that we need to ban mental language from AI altogether. That would be unrealistic and probably unnecessary. Human beings explain unfamiliar things by comparison. We anthropomorphize, simplify, and speak loosely because that is part of how language works. The point is that we should not let loose language become literal without noticing.
AI can produce answers that look like the products of thought. It can respond in ways that resemble understanding. It can imitate reasoning, explanation, and judgment with increasing fluency. But resemblance is not identity. A system may behave as if it thinks without thinking in the ordinary human sense. Those two words, “as if,” are not a minor qualification. They are the line between metaphor and mistake.
This is why the real question may not be whether AI can think. At least, not at first. The question is what we are willing to say about AI, and what our words make it easier for us to believe. Are we describing a tool, or are we slowly talking ourselves into seeing a mind? Are we naming what is there, or are we being led by the metaphors we forgot were metaphors?
I will probably keep using AI almost every day. I will probably keep choosing the “thinking” model when I have a complicated question. The label is useful, and I know what it means in practice. But I also want to remember that clicking on a word is not the same as discovering a mind.
Maybe that is where we should begin: not by asking whether AI is thinking, but by asking whether we are being careful enough with the words we use.
Written by Matt Fujimoto
Featured Medium Writer, Editor, and Boost Nominator | Philosopher | Find Me Everywhere: https://linktr.ee/mattfujimoto
Published in Philosophy Today
Philosophy Today is dedicated to current philosophy, logic, and thought.
本文於 修改第 2 次
|
|
「意思」、指涉論、和相對觀 -- Paul Austin Murphy
|
|
|
推薦1 |
|
|
|
我對下文所討論的主題有些興趣；但沒有去深入了解，也沒有花很多時間來思考。請參見拙作：《「意思」和「翻譯」 -- 兼評《哲學辭典》中譯本》和《淺談相對觀和社會建構論》。
How Philosophers of Reference Saved the World from Relativism
When Kuhn and others questioned realism in science, the “tool” of reference was used to argue that the world is not well lost.
Paul Austin Murphy, 06/09/26
The following passage expresses what was at stake after Thomas Kuhn’s own “revolution”:
“[W]e need an alternative account of meaning which allows that people holding competing or successive theories may still be talking about the same thing.”
Partly as a reaction to what many took to be “Kuhnian relativism”, some philosophers wanted to find a means of fighting back. They did so by focusing on reference.
Meaning always (or often) goes alongside reference in this tradition. But “what then is the constant in meaning?” According to the historian and philosopher of science Ian Hacking, Hilary Putnam “makes everything turn on reference and extension”.
The most obvious thing to say here is that these philosophers were attempting to securely tie names, words and terms to the world.
Fregean Sense
Long before Kuhn and Putnam, Gottlob Frege “thought that a word has a standard sense, which is what makes a scientific tradition possible”. What is that sense? —
“The sense is what is shared by all communicators, and may be passed down from generation to generation of students.”
It will be shown that Hilary Putnam’s “stereotype” (to be discussed in a moment) shares a family resemblance to Frege’s sense. (They’re still very different notions.) Still, what is important here is that Frege
“taught us that an expression should have a definite fixed sense, which we apprehend, and which enables us to pick out the reference”.
In other words, the route a word/term takes to a thing goes via this fixed sense.
Hacking’s Own Position on Reference
Sometimes it’s difficult to decipher if Hacking is putting his own view or that of someone else (e.g., Putnam). In this case, he puts the case for the permanence of reference in the following way:
“If we do have a genuine natural kind term, the reference of the term will remain the same, even though stereotypical opinions of the kind may change. Thus the fundamental principle of identity for a term shifts from Fregeian sense to Putnamian reference.”
We’re told that the reference (miraculously?) remains the same even though what are deemed to be its stereotypical properties change. The claim here isn’t that the reference can be “found” without relying on its stereotypical properties, only that such properties change. The obvious question now is:
If the stereotypical properties are always changing, how do we know we have the same reference?
The Putnamian position is that we get at the reference via his version of “Fregean sense”. The Fregean sense “may change”, while the reference, qua reference, doesn’t. However, does that really answer the question (in color font) above?
To be clear. Hacking accepts the importance of reference for science. However, he tells his readers that “[a]nybody who thinks that reference works by a causal and historical connection to the thing named ought to reflect on the following example”. Hacking then gives a complex historical example in which the notion of “causal and historical connection to the thing named” doesn’t work, but Hacking’s own entity realism does.
So this isn’t an attack on reference. It’s an attack on a particular account of reference.
Hacking on Acid
Hacking provides a concrete example of possible incommensurability as it relates to the word ‘acid’:
“The incommensurabilist would say that we mean something different by the word ‘acid’ than did Lavoisier or Dalton around 1800. Our theories about acids have changed substantially [ ].”
Of course, this is very difficult for the layperson to grasp because he’d need to have both historical knowledge and a knowledge of chemistry. It would work very differently if, say, Hacking gave as an example the word ‘cat’ or ‘brick’. Yet even the layperson would probably accept the clause “our theories about acids have changed substantially”.
In any case, Hacking continues:
“[ ] Putnam says, we are still talking about the same kind of stuff as those pioneers of the new chemistry.”
Intuitively, and simply, this seems feasible. It could be a case of people saying different things about the same stuff. Even contemporary persons could be saying different things about the same stuff.
This position posits a kind of strong distinction between the stuff itself and what we say about it. Can that distinction be maintained? Wouldn’t it assume that firstly we have uncontaminated stuff, and, later, our sayings about it? What if that stuff is always contaminated with sayings or theories? That may be the case. Yet the same stuff would still underpin all these different sayings and theories.
Reference and extension are means to hold on to that same stuff.
Putnam’s Stereotypes
According to Hacking, Putnam justified his position in terms of what he called a “stereotype”:
“Certainly there is an important cluster of properties and in the professional stereotype for acids: acids are substances that in a water solution taste sour, and change the colour of indicators such as litmus paper. They react with many metals to form hydrogen, and react with bases to form salts.”
That’s a decent number of properties we can use to identify acids. Is this a roundabout way of saying that everyone in the know will experience a sour taste, experience a litmus paper changing to a certain colour, etc. regardless of whether they lived in 1800 or 2020? This would mean that any disagreements about acids must occur elsewhere — beyond these specific properties. It seems that the differences in theory account for these differences.
Hacking mentions theory in the following:
“Lavoisier and Dalton would agree completely with this stereotype. Lavoisier happened to have a false theory about such substances, for he thought every acid had oxygen in it.”
So we have different theorists all experiencing a water solution tasting sour, indicators such as litmus paper changing colour, stuff reacting with many metals to form hydrogen, and the stuff reacting with bases to form salts. Over and above all that, we have theory too.
(Just to get this point across, let’s take Putnam’s other example of the word ‘water’. Putnam “gives us colourless, transparent, tasteless, thirst-quenching, etc [as] part of the stereotype for ‘water’”.)
One question readers may ask here is whether or not all these properties (or stereotypes) really are theory-free. After all, we’re taking about hydrogen, oxygen, litmus paper, salt, etc. here. Perhaps that doesn’t matter in this specific context.
Hacking concludes with a entity-realist statement: “But there is no doubt that Lavoisier and Davy were talking about the same stuff.”
Davy is mentioned here because in 1810 he showed that Lavoisier’s theory “was a mistake”. That is because “muriatic acid is just HC1, what we now call hydrochloric acid”. Here again we’re shown that theory rides piggyback on these stereotypical properties of the stuff. Indeed, the new term “hydrochloric acid” does so too.
These general points are made again by Hacking as he states that
“the philosopher of naming must ask if Lavoisier meant Brønsted-Lowry acids or Lewis acids when he spoke of acids.”
Here’s the crunch: “Obviously he meant neither.”
That means that there is a distinction to be made, again, between stereotypical properties and theories. Can we now say that Brønsted-Lowry acids and Lewis acids are theory-laden, but stereotypical properties aren’t? (The philosopher Russell Hanson, way back in the 1960s, would have certainly said, ‘No, we can’t.”)
Bas van Fraaseen’s Electron
A much-better known case of naming is the electron. Hacking writes:
“[Bas van Fraassen] does tease the realist, who is confident that there are electrons: ‘Whose electron did Millikan observe; Lorenz’s, Rutherford’s, Bohr’s or Schrodinger’s?’”
On our theme of theories, isn’t the Dutch-American philosopher Bas van Fraassen referring to the different theories of the electron, not to the electron itself? After all, don’t we have the phrase “different theories of the electron”, not “different theories of the banana”. That said, what the hell is this theory-free electron? There’s nothing more theory-laden than the electron, surely. Tell me, what is the electron without theory? It was born with theories attached to it. It has never been free of theory. The realist, or Putnam, may concede all this. But that still leaves stereotypical properties which run free of theory… Or do they?
Now take the (entity) realist’s “obvious reply”, at least as expressed by Hacking:
“Millikan measured the charge of the electron. Lorentz, Rutherford, Bohr, Schrodinger and Millikan were all talking about electrons. They had different theories about electrons. Different stereotypes of electrons have been in vogue but it is the reference that fixes the sameness of what we are talking about.”
It’s not just that theories about any given x change, so too do the stereotypical properties. Hacking is saying that we have something, “the reference” (or the electron), which is free of not only theory, but also any fixed set of stereotypical properties. Isn’t it this position that really irks the anti-realist or instrumentalist? What can we say about the reference without any stereotypical properties or theory? Perhaps, then, Hacking isn’t arguing that we do have the reference (or electron) without any stereotypical properties. It’s just that such properties can change. That is, they can be “in vogue” this week, and out of vogue next week.
We can now take a slightly different approach to the importance of reference — one that doesn’t actually focus on scientific terms.
Donnellan’s Causal Theory of Reference
The philosopher Keith Donnellan attempted to save philosophical realism via reference. In other words, if we can have a causal theory of reference which excludes names like ‘Santa’, then we can distinguish real propositions like “Lady Gaga will come tonight” from “Zeus is angry with us”.
Donnellan argued that proper names shouldn’t rely on being tied to “descriptive content”. Metaphorically, he believed that this would give individual minds too much power, and direct causal reference less power.
Associating descriptive content with proper names has been deemed to be idealist by some philosophers too. (“Subjective” or “mentalist” is a better term in this context.) A causal connection to Lady Gaga (or the ‘Lady Gaga’ relation to Lady Gaga) is concrete. The descriptive content “The rubbish [or great] singer in Hollywood” is subjective, or at least dependent on an individual mind (or on individual minds in the plural). Similarly, the definite description that readers personally tie to the name ‘Santa’ may be very different to the ones other people tie to that name.
So what would secure us identity of reference here when it comes to the names ‘Santa’ and ‘Lady Gaga’?
Donnellan’s causal theory of reference (which excludes Santa) is the realist’s way of avoiding not just idealism (or, better, subjectivity), but also relativism.
Conventions, conceptual schemes, identifying descriptions, etc. were deemed to be subjective by Donnellan. Causal processes, on the other hand, are deemed to impose themselves on us. In other words, they tie us firmly to the world.
Written by Paul Austin Murphy
MY PHILOSOPHY: https://paulaustinmurphypam.blogspot.com/ My Flickr Account: https://www.flickr.com/photos/193304911@N06/
本文於 修改第 1 次
|
|
文字起源新知--Colin Barras
|
|
|
推薦1 |
|
|
|
對語言、文字起源有興趣的朋友來說，下文無疑是遲來的珍貴資訊。轉載於此。
A lost ancient script reveals how writing as we know it really began
A long-overlooked writing system from 5000 years ago is still largely undeciphered, but could mark the moment humans first represented their speech with written words
Colin Barras, 05/04/26
Early writing is a tale of two scripts. Egyptian hieroglyphs and Mesopotamian cuneiform both emerged independently about 5300 years ago. The political powers of ancient Egypt and Mesopotamia flourished in the centuries to come, partly because writing helped states control the flow of goods and consolidate power. The pen (or ancient stylus) was mightier than the sword.
Or so the conventional story goes. But there is a glaring omission here because, at the dawn of writing, there weren’t two scripts. There were three. That third, mysterious script, called proto-Elamite, appeared in ancient Iran while cuneiform and hieroglyphs were both in their infancy – and has been shockingly overlooked by all but a handful of scholars since its discovery 125 years ago.
That is beginning to change, with far-reaching consequences. Although proto-Elamite remains largely undeciphered, there is tantalising evidence that it became by far the most advanced of the three scripts in operation about 5000 years ago. What we now know about the script’s story is so surprising and counterintuitive that we might need to rewrite the early history of writing.
Remarkably, this obscure writing system could represent a giant leap forward in how we represent speech in written form. Spoken language might be 1.7 million years old, but it wasn’t until proto-Elamite that we may finally have been able to start writing down exactly what we were saying. So why, then, did this incredible script vanish not long after it was invented?
Proto-Elamite writing tablets have been turning up at archaeological sites across the Iranian plateau since 1899. Most were found at the ancient city of Susa, which is associated with the Elam culture that appeared about 4500 years ago. But the tablets predate the rise of Elam, which is why the writing system has been named proto-Elamite. The latest thinking is that the oldest tablets are about 5200 years old, suggesting they slightly postdate the earliest texts written using Egyptian hieroglyphs or an early version of cuneiform dubbed proto-cuneiform.
Proto-Elamite was probably inspired by proto-cuneiform, according to Jacob Dahl at the University of Oxford. This is hardly surprising, given that Susa – now long abandoned – is just a few hundred kilometres from the ancient Mesopotamian city of Uruk, which was a major centre of proto-cuneiform writing. Just like the Mesopotamian script, proto-Elamite was inscribed into wet clay using a stylus, and some signs are almost identical, such as the one for “sheep” – a cross inside a circle. The ancient scripts were used in a similar way, too, primarily to keep economic records.
There are, however, other ways to interpret the origins of proto-Elamite. Dating ancient clay tablets can be tricky, partly because many were dug up more than a century ago during less-than-meticulous excavations. As a result, some researchers think it is possible that proto-Elamite is just as old as the other two writing systems, with all three emerging independently. Here, the similarities with proto-cuneiform are explained by both scripts borrowing signs and conventions from earlier, pre-writing systems used across south-west Asia. “I would struggle to say one writing system follows the other,” says Amy Richardson at the University of Reading, UK.
A proto-Elamite tablet, around 5000 years old, shows the yields of crops from five fields；Jacob L. Dahl, University of Oxford 照片
Regardless of its exact origins, proto-Elamite is a far more obscure and mysterious writing system than proto-cuneiform. Even today, it remains largely undeciphered. Although we know how numbers were written (see “Complex counting“), it isn’t clear what most of its non-numerical signs represented. This is partly because of the choices ancient Iranian scribes made when inventing the script. While many proto-cuneiform signs are clearly pictures that hint at each sign’s meaning – a human hand to represent “give” or a spiked stem to represent “barley” – proto-Elamite signs are typically more abstract, so it is far less obvious what they represent.
This feature does, however, give proto-Elamite a surprisingly modern appearance, given that the signs and letters in most of today’s writing systems are also abstract. This air of modernity is enhanced by the fact that ancient Iranian scribes wrote in lines, which were read from right to left. Mesopotamian scribes had a more complex writing process in which information was encoded in boxes, which makes proto-cuneiform tablets look a little like the output of a spreadsheet app rather than a word-processing program.
Complex counting
Proto-Elamite may not be fully deciphered, but we do know it included an astonishing variety of numerical systems, and the way objects were counted depended on what they were. One striking discovery is that people were counted differently depending on their social status. Labourers were counted using a decimal system that was also used to tally common livestock, whereas high-status individuals were counted using a sexagesimal system (based around divisions of 60).
Dahl’s work over the past 25 years has transformed our understanding of proto-Elamite. In the early 2000s, he and his then-doctoral supervisor, the late Robert Englund, began a project to digitise all 1700 known proto-Elamite texts and make them freely available online for study.
Through careful analysis of the original clay tablets, Dahl has also produced and refined a list of proto-Elamite’s non-numerical signs. Their exact number isn’t clear, because it is difficult to determine whether two slightly different signs are truly distinct or whether they simply show allowable variation within a single sign.
A proto-Elamite dictionary
Dahl’s current estimate is that proto-Elamite signs numbered in the hundreds to low thousands. The hope is that patterns in the way these signs appear in the texts will help us define a great many of them, effectively giving us a proto-Elamite dictionary that we can then use to read the tablets.
Initial work is encouraging. For instance, one challenge has been to identify the sign for “cow”, an animal we know was important to the ancient Iranian economy because archaeologists have found cattle bones at many sites. One sign has been tentatively identified as a “cow” sign – but, strikingly, it never appears on tablets bearing a sign that we know means “plough”. This might suggest the “cow” sign proposal is wrong.
But over the past five years, a team including Kathryn Kelley at Uppsala University in Sweden and Logan Born, formerly at Simon Fraser University in Canada, has analysed Dahl’s online archive of proto-Elamite texts using computer software. The team’s work has identified a strong but hidden connection between the “plough” and proposed “cow” signs. Despite never co-occurring, both are members of a broader group of signs that do appear together – signs that presumably are linked to the world of farming.
The software analysis revealed other features, too. The ancient scribes sometimes placed one sign inside another – a little like placing a letter “A” inside a letter “O”. The exact meaning of these combined signs is unclear, but seems to indicate an overlooked “grammar” in the way combinations of characters were made. These combinations are found on tablets at sites across what is now Iran, suggesting there was a degree of standardisation in how different scribes followed proto-Elamite’s rules.
Despite such work, progress towards decipherment is slow. Even so, the researchers who have studied the script largely agree on one point: proto-Elamite was by far the most advanced writing system in operation 5000 years ago.
Writing at this early stage was incredibly simple. With little more than a collection of signs representing ideas to work with, scribes could record information only in note form – for instance, using the signs “man”, “goat” and “50” to document that a particular person had a herd of 50 goats. But there is evidence that proto-Elamite had escaped this limitation, and that ancient Iranian scribes had begun to use signs to encode spoken language.
Dr Jacob L. Dahl, University of Oxford 照片
It is difficult to overstate what a significant breakthrough this was. Spoken language may be up to 1.7 million years old, and it has evolved into a complex and nuanced communication system. When writing began encoding speech, it instantly gained most of that complexity. “It piggybacked on the amazing functionality of language to communicate,” says Piers Kelly at the University of New England in Australia. Today, we take for granted that writing can be used to persuade, delight or anger a reader – but it can do so only because it encodes speech.
In fact, Kelly and many other researchers argue that encoding speech isn’t just an important feature of writing, but its defining one. This would mean that scripts like proto-cuneiform that don’t encode speech aren’t really writing at all. Accept that argument and proto-Elamite – if it really did encode spoken language – was the world’s first true writing system.
Evidence for this language encoding comes from proto-Elamite tablets in which non-numerical signs occur in curious sequences between four and 12 signs long. These sequences are difficult to explain if the signs represent objects. But they would make more sense if the signs instead represented syllables in long, multisyllabic words – almost certainly the names of important people.
Additional support for the proposal comes from Dahl’s work on the proto-Elamite sign list. It turns out that ancient scribes used a subset of about 100 signs to write the curious sequences. This number is significant because many spoken languages are constructed from roughly this number of distinct syllable sounds, so writing systems that record a language’s syllabic speech in full often contain between 40 and 100 signs (see “Three ways to write”).
The remains of the ancient city of Susa, in what is now Iran, where many proto-Elamite tablets were found；LiviusOrg/Jona Lendering 照片
“If those signs really are an early syllabary, that would be so exciting,” says Dahl, given that Egyptian hieroglyphs and Mesopotamian cuneiform didn’t encode syllabic speech in full for another 500 years. He cautions, however, that it is just an idea, albeit a popular one.
But if the ancient Iranians did invent the most advanced writing system of their time, what happened next? Over the past few years, two very different scenarios have emerged.
The first is both exciting and profound. It suggests the ancient Iranians began a long-lasting relationship with writing similar to that seen in Mesopotamia and ancient Egypt. “We are dealing with three cradles of writing,” says François Desset at the University of Liège in Belgium.
Desset reached this conclusion partly through his work on another ancient Iranian script that was discovered during excavations at Susa 125 years ago. This script, known as Linear Elamite, was in use in ancient Iran about 4100 years ago.
An Elamite Rosetta stone 照片
Linear Elamite has long been considered just as mysterious as the proto-Elamite script. Then, in 2020, Desset announced that he had successfully deciphered Linear Elamite. He realised that the Linear Elamite texts inscribed onto a set of silver goblets were prayers – and that we already knew the contents of those prayers because they also appear on another set of goblets, but written using a readable script. By comparing the two sets of goblets, Desset worked out how to read Linear Elamite. The approach is similar to the way in which Egyptian hieroglyphs were deciphered using copies of the same text written in different scripts on the Rosetta stone.
Desset worked out that the Linear Elamite signs encode syllables, and he began assigning sound values – “ha”, “pe”, “su” and so on – to each one. “I can read about 96 per cent of the signs in the inscriptions,” he says.
Silver vessels with inscriptions in Linear Elamite, which some researchers think developed from proto-Elamite; others think there is no link；F. Desset/Mahboubian Collection 照片
He and his colleagues gave details of this decipherment in a 2022 study. But the researchers made an additional claim in their work. They highlighted similarities in the appearance of some Linear Elamite and proto-Elamite signs, arguing that this is evidence that the two scripts are actually the same writing system at different stages in its development. “There is a continuity of the scribal tradition on the Iranian plateau, which was mostly overlooked up to now,” says Desset.
Other researchers, including Dahl, are sceptical of this claim, instead arguing that a different scenario played out all those years ago. They think that shortly after proto-Elamite became potentially the most advanced script of its day, the ancient Iranians abandoned it and gave up writing. “They simply rejected it,” says Dahl.
He says this scenario fits with the evidence – or rather, the lack of evidence. There is very little in the archaeological record to suggest that the ancient Iranians wrote down anything between 4900 and 4100 years ago. One or two disputed examples aside, we know of no proto-Elamite or Linear Elamite texts from this 800-year period.
This suggests to Dahl that Linear Elamite wasn’t a continuation of proto-Elamite, but a distinct and independent invention of writing – perhaps recycling some of the signs found on long-discarded tablets. This scenario is arguably far more surprising than the one outlined by Desset and his colleagues, because it doesn’t fit with modern thinking on literacy. It is difficult for us to imagine a society willingly discarding writing – particularly a script that had potentially made an enormous technological leap by encoding speech. But such a rejection actually fits well with an ongoing reassessment of human history.
Over the past five years, archaeologists have begun questioning long-held assumptions. Where once they traced a simple path from ancient hunter-gatherers to early farmers to the rise of civilisations, they now accept that the story was more complicated. For instance, while farming was practised in Britain when Stonehenge was built 5100 years ago, populations then reverted to hunter-gathering. Societies don’t all make the same choices, and even two societies that follow the same path don’t necessarily continue to develop in the same way.
Ditching writing
Dahl suspects this explains why writing failed to take hold in ancient Iran. In recent years, he and one of his colleagues at the University of Oxford, Parsa Daneshmand, have both published articles suggesting that ancient Iranians chose to reject writing because words are often used to control populations. “Proto-Elamite was a repressive system, a way to keep track of goods and allow those in charge to say: ‘You didn’t bring in enough,’” says Dahl. It was probably extremely unpopular.
The same was presumably true of proto-cuneiform and early Egyptian hieroglyphs, which means the real surprise isn’t that proto-Elamite failed, but that the other two writing systems succeeded. Perhaps, says Dahl, they did so because the elites who benefited from writing lost power in ancient Iran, but maintained control in Mesopotamia and ancient Egypt.
It is worth considering both Desset’s and Dahl’s scenarios for the fate of proto-Elamite, says Kelley. “With an undeciphered script, you should always explore every option.” But she and many other researchers find Dahl’s scenario more plausible. This isn’t just because there seems to be an 800-year writing gap in the ancient Iranian archaeological record. It is also because the ancient Iranians were apparently unenthusiastic about literacy even when they did write.
A proto-cuneiform tablet from around 5,000 years ago records beer rations；The Trustees of the British Museum 照片
For instance, almost from the moment Mesopotamians began writing, there is evidence they invested heavily in the idea: archaeologists have found plenty of proto-cuneiform tablets that were clearly teaching aids, designed to train more scribes and embed a writing tradition in Mesopotamia’s urban centres. In contrast, there are no known proto-Elamite teaching texts.
“Proto-Elamite was never particularly committed to in the same way that we possibly see with proto-cuneiform,” says Richardson.
This lack of commitment is also reflected in the number of texts. Although there are 1700 known proto-Elamite tablets, this is a small number compared with the 8000 proto-cuneiform tablets. Linear Elamite was used even more sparingly: only about 40 short inscriptions have been discovered.
But in a final twist, ancient Iran’s aversion to writing didn’t hold it back. In fact, the illiterate ancient Iranians grew more powerful than their literate Mesopotamian neighbours.
“If you go down to the Sukkalmah period [around 3800 years ago], there’s no doubt that Mesopotamians look at Iran and say: ‘They are far more important than we are. They’re stronger and richer than we’ll ever be,’” says Dahl. “They actually call the king of Elam ‘our father’.”
But, says Dahl, the king of Elam had little interest in writing. Even in an increasingly literate world, he – and his subjects – knew that writing wasn’t essential for success.
Three ways to write
There are three basic categories of writing systems, which can be distinguished by looking at the number of distinct signs in the script.
Logographic scripts: Signs represent words or ideas. These writing systems may have 1000 or more signs. Examples include Egyptian hieroglyphs and Chinese characters.
Syllabic scripts: Signs represent spoken syllables. Because most spoken languages contain a limited number of distinct syllable sounds, these scripts usually contain no more than 100 signs. Examples include Japanese, Cherokee and, potentially, the proto-Elamite used in ancient Iran.
Alphabetic scripts: Signs represent phonemes, the basic units of speech. Most spoken languages have a restricted range of distinct phonemes, so alphabets may contain fewer than 30 signs. Examples include Latin, Greek and Arabic.
Subscriber-only newsletter
Sign up to Our Human Story：Each month, Michael Marshall unearths the latest news and ideas about ancient humans, evolution, archaeology and more.
Sign up to newsletter
相關閱讀：
* How the secrets of ancient cuneiform texts are being revealed by AI
* The remarkable tale of how humans nearly didn’t conquer the world
* Over tens of thousands of years, waves of Homo sapiens set out across Europe and Asia, only for their societies and cultures to mysteriously vanish. At last, ancient DNA is revealing why
本文於 修改第 1 次
|
|
左右語言演變的四個普遍模式 - Ryan Whalen
|
|
|
推薦1 |
|
|
|
可惜下文沒有詳細說明：這四個「出人意料法則」的內容。
Universal Patterns Emerge in Human Languages, Revealing “Four Surprising Laws” Behind Their Evolution
Ryan Whalen,·04/30/26
Human languages as disparate as English, Japanese, and Russian follow remarkably similar evolutionary paths, according to a new AI study, which investigated how new concepts were added over time.
Researchers from Fudan, Harvard, and Stony Brook Universities revealed their findings in a recent paper published in the Proceedings of the Royal Society B, based on their work across 21 languages, many of which are separated by time, going back to the medieval period, as well as distance.
The work used word embeddings in a natural language processing algorithm, which analyzed a wide range of languages to determine their hidden evolutionary connections.
Universal Language
“We are looking for insight into fairly universal questions of how people develop concepts that they feel are worth naming,” Dr. Steven Skiena told The Debrief. “Words are examples of named concepts, and thus the right level to address our study. By proving that the same phenomena holds across many languages, we show that this process is indeed universal in some sense as opposed to culture-specific.”
While languages may have unique sounds and grammar rules, the new work examines similarities in how languages evolve on a large scale, seeking universal properties across disparate languages as more words are added.
“New words, concepts, and ideas are generated all the time,” Dr. Skiena explained. “But do hidden patterns exist that govern which concepts are likely to emerge? And are there simple mathematical models that emulate this process?”
AI Language Tools
“We were inspired by the idea that AI technologies for representing language semantics (word embeddings) give us a rigorous way to reason about the evolution of language,” Dr. Skiena said. “With word embeddings, each distinct vocabulary is associated with a particular point in a high-dimensional feature space. Words with similar meanings are represented by nearby points.”
“In essence,” Dr. Skiena continued, “our paper asks how the vocabulary of languages distributed in this feature space, and what kind of mathematical process would create a similar distribution.”
To perform their work, the researchers needed large-scale word embedding datasets for each of the included languages, which had a major impact on the language selections for the research. Since their research focused on the evolution of language, they included many historical datasets, with embeddings representing languages dating back to the Middle Ages, preferring the greatest possible historical depth. The challenge was producing a model that captured how real languages evolve.
“We wanted to prove that certain mathematical models generated embedding spaces that look very much like real natural languages,” Dr. Skiena said. “But what do real natural languages look like?”
“We had to develop a set of four surprising laws/principles that govern the structure of real languages,” Dr. Skiena added, “and then prove that our favored mathematical model generates embedding spaces that also had these unusual properties.”
Language Analysis Results
“I think of cultural influences as the force that shapes the evolution of languages, but it is clear that the brain shapes these cultural influences,” Dr. Skiena said, regarding the similarities the researchers found among different languages. Co-author Dr. Sergiy Verstyuk added, in a conversation with The Debrief, that although there are potential connections between their work and neuroscience studies, that was not the direct aim of their work.
Among the commonalities the researchers discovered was that popular words were often clustered with other popular words in specific regions of the mathematical space. Additionally, the hierarchy of this type of clustering was quite similar between many languages. Word creation usually occurred in bursts, with recent words surrounding other recent words, as new concepts entered the vernacular, similar to the periodicity of rapid change in biological evolution.
“One important aspect of our work is that we constructed a surprisingly simple model that not only replicates the earlier results on the power-law distribution of word frequencies, but that also accounts for new empirical findings across many additional dimensions (specifically, in the 300-dimensional semantic space and in historical time),” explained Verstyuk. “This was done by marrying a well-known cumulative‑advantage process with a far less often used von Mises–Fisher probability distribution.”
“This paper has had an amazingly long gestation: we have been working on this together for more than seven years at this point,” Dr. Skiena concluded. “But it is great to see where we have finally gotten to. I am not sure we are ready to wait another seven years for the next paper. We remain excited about the possibilities of using AI-generated embeddings as a tool for fundamental research in understanding historical processes in cultural evolution, not just for building technological tools.”
The paper, “Statistical Structure and the Evolution of Languages,” appeared in Proceedings of the Royal Society B on April 08, 2026.
Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.
See Also
Scientists Develop Breakthrough “DNA Origami” Nanobots That Can Precisely Target and Kill Cancer Cells
本文於 修改第 1 次
|
|
「共通語言」的淵源和展望 -- Alexandra Aikhenvald
|
|
|
推薦1 |
|
|
|
索引：
Creole language：克里奧爾語
lingua franca：「共通語言」指「通用」於不同母語人群之間的「語言」。
pidgin language：皮欽語
What is a lingua franca? A brief history, from the Crusades to today
Alexandra Aikhenvald, 04/21/26
When the Crusaders descended upon the eastern shores of the Mediterranean at the end of the 11th century, they had to communicate with each other, with traders and with locals.
Many of them spoke different Romance languages: Italian (especially from the then powerful city-states of Venice and Genoa), Provençal, French or their forerunner, Latin.
Most Westerners in southern Europe were French, especially from between Marseilles and Genoa, from where ships and traders sailed towards the Middle East. These Westerners, as a whole, came to be called Franci (Franks, or French) by Arabs and Greeks.
Around the time of the Fourth Crusade (1202–04) – and perhaps earlier – a mixed language gradually emerged in the eastern Mediterranean, and later spread to the west.
This common language used by the “Franks” and those who traded and fought with them was also known as Sabir, Bastard Italian and Bastard Spanish. But you might be most familiar with the term Lingua Franca: literally, Franks’ language.
The Frankish language was a mixture of simplified Italian, French and Spanish, with a smattering of Arabic and Turkish, and was in use across the Mediterranean shores in the Middle East until the late 19th century, before it faded away.
Written with lower case, lingua franca refers to any language used between people who have no other language in common.
An ancient tradition
Lingua francas go back to antiquity.
Sanskrit was a lingua franca throughout Southeast Asia and Central Asia in the first millennium CE, via trade and religion.
Around the Mediterranean, Greek was a lingua franca from about 300 BCE until about 500 CE, used in trade, literature and education, and in spreading early Christianity.
Between the second and the fourth centuries, standard Latin replaced Greek as the lingua franca of the expanding Catholic Church. Latin took over as the pan-European language of religion, culture and scholarship, and continued well into the 19th century.
Latin became the European lingua franca, as demonstrated on this 12th century British pendant. The Metropolitan Museum of Art
From the 17th century, Arabic has been a lingua franca across the Islamic world, connecting communities across Africa and Asia.
That same century, with the rise of France as an economic power, French gradually replaced Latin in many areas as the first “global” lingua franca in politics, diplomacy, trade and education. French was the language of royal courts; scholars, aristocrats, merchants, and diplomats would use French to talk and to write to each other.
French continued to be the main language of international relations up until the end of the second world war.
After the 1940s, partly due to the growing influence of the United States, English has become the main lingua franca across the world.
Crafting a new language
With the colonial expansion of imperialistic powers and their languages Spanish, English, French, Portuguese, German and Dutch, since about 15th century, the name lingua franca came to be used as a common noun.
Throughout European colonisation, people from different language groups were forced to work together as slaves or indentured workers. They would communicate with each other, and with their masters, using a simplified language, for limited purposes – simple commands, questions and statements using a mixture of what each of them knew.
Such makeshift means of communication is known as pidgin language (from the English word business).
Pidgins can be used as lingua francas. Once speakers of a pidgin start marrying each other, a pidgin may become the sole language spoken by the next generation of children. It then expands into a fully-fledged language – a Creole – used for all purposes.
Creoles such as Tok Pisin in Papua New Guinea, Sranan in Suriname, Kristang in Malaysia, and Haitian Creole in Haiti are lingua francas used across these countries.
The Atlantic–Congo and French-based Haitian Creole is spoken across the island nation. AP Photo/Ramon Espinosa 照片
A global language can also be of artificial origin.
The end of the 19th century saw an explosion of interest in constructing global languages. The most prominent of these was Esperanto, “the language of hope”, created by Ludwik Zamenhof in 1887 as “the international language”, or a general lingua franca. Esperanto still boasts a couple of thousand native speakers, and many more enthusiasts, but is gradually on the wane.
Today’s global lingua franca
Lingua francas arise when required, and fade when replaced by others.
German faded as a lingua franca with the loss of German colonies after the first world war. Portuguese remains a lingua franca across Brazil, and Spanish across other South American countries.
And the global use of French is still there: we send a letter par avion, or to poste restante.
But there is one winner, well ahead of the rest. English has now grown to be the global language, spreading well beyond native speakers and the former colonies of English-speaking powers. English is the language of world-wide diplomacy, scholarship, and especially technological advances, social media and artificial intelligence.
Does the aggressive spread of English threaten to put an end to all other languages, minority languages and other lingua franca alike, and language diversity across the world? The jury is still out.
The growing importance of Mandarin Chinese as a main lingua franca across China, of Arabic across Africa and the Middle East, and people’s resilience to keep their languages going – and with them their cultures and histories – may well keep English at bay.
Alexandra Aikhenvald is the Professor and Australian Laureate Fellow, Jawun Research Institute, CQUniversity Australia
本文於 修改第 1 次
|
|
語言功能：了解「意在言外」 - The Female Code
|
|
|
推薦1 |
|
|
|
我轉載這篇文章的目的是提醒：「語言的『多功能』性質」；以及顯示：奧斯汀的「語言等同行動理論」。故置於此欄。
不過，我們為人處世總要留點空間；畢竟，不是每個光棍都有資格自以為是「黃金單身漢」。因此，掌握「語言的『多功能』性質」，加上堅持「事不過三」這個底線，或許可以幫助各位在處對象過程中不受傷害，又能找到最般配的另一半。
The 4 Words Women Use to Control You (Before You Even Notice What’s Happening)
Learn the subtle language that reveals her true intentions — and regain control before you get emotionally played.
The Female Code, 12/02/25
It happens all the time.
You meet a woman, the connection is strong, the chemistry is electric, and then… something shifts. The energy changes. You start feeling less like an equal partner in the dynamic and more like a hopeful spectator watching her life from the sidelines.
So many confusing signals.
Most men assume that manipulation or a woman’s disinterest always shows up in grand, dramatic actions — the silence, the mixed signals, the obvious “games.” But the truth is far more subtle and far more insidious.
The real game hides in language.
The Silent Power of Linguistic Framing
Language is influence. Whoever shapes the meaning of an interaction controls the emotional dynamic that follows. Psychologists call this linguistic framing, and it’s a powerful tool. A single phrase, a carefully chosen word, can fundamentally change how you feel about the situation before your conscious mind even realizes what’s happening.
Women understand this instinctively. When she controls the words, she controls the emotion that is triggered in you. It’s not about what she says; it’s about what that word signals regarding your value and position in her life.
This is why you feel so frustrated. You hear what she says, but you’re blind to what she’s signaling.
Once you learn to recognize these linguistic patterns — the four subtle words that are indicators of leverage, not connection — everything changes. You stop reacting to her words and start reading her actual intentions.
Let’s break down the four phrases that women use to establish control before they start draining your emotional resources and, more importantly, how to flip the script immediately.
1.“I’ve just been so busy.”
“Busy” is the ultimate word of control. When she constantly replies, “I’ve just been so busy,” she is not complaining about her schedule; she is activating a screening process. She’s testing how much effort you will invest with a minimal or nonexistent reward.
The immediate pain point for most men is thinking, “If I just wait patiently, she’ll make time for me.”
But that’s not the mechanism at play. She is gauging your patience, because to her, patience equals submission. She’s conditioning you through a classic behavioral science principle known as intermittent attention. Behavioral scientist B.F. Skinner proved decades ago that unpredictable rewards create the strongest, most enduring pursuit.
You text. She delays. She finally replies just enough to reset your hope, and your brain lights up like you’ve won a prize, even though you’ve won nothing at all. She is conditioning you to chase her absence.
The Flip: Silence the Tension
You don’t need to confront her. You don’t need to explain your frustration or demand a better schedule. You simply stop showing up.
Silence creates the same tension she tried to control. When she realizes she can’t provoke a reaction, her “busy” narrative collapses. Her schedule suddenly clears up, because the man who refuses to compete for her time is the one she is forced to start competing for.
2.“Maybe, I’ll let you know.”
Maybe is the softest, most comfortable cage she can put you in. It’s not a yes, and it’s not a firm no; it is a hold.
When she uses this word, she’s essentially keeping you accessible and on standby while she checks her other options or prioritizes different plans. This is a measure of her power — she’s gauging if you will stay utterly accessible and without direction, seeing if your self-respect bends when her attention disappears.
The pain point here is that men confuse silence with being polite. You think waiting shows interest, but waiting only shows weakness. Your time is, in fact, finite and valuable. When you give her an endless window of accessibility, you signal that you have no other priorities.
The Flip: Treat Maybe as No
Correct this immediately by treating “maybe” as an absolute no.
Do this not with attitude or resentment, but with utter certainty. You are simply moving on with your life and making other plans. When you act like your time is inherently limited and valuable — because it is — she is forced to treat it that way, too.
The moment she realizes she cannot stall you, she has two inevitable options:
she either commits and locks down a real plan, or
she loses you entirely.
In both scenarios, your power is fully restored.
3.“You’re such a good friend.”
Friend is not a connection; it is a demotion.
When she labels you a “good friend,” she is not being nice; she is definitely labeling your position. Women categorize men immediately: dominant, provider, placeholder (備胎), or emotional outlet (發洩情緒對象). Friend means she views you as a resource without reward.
You become her emotional sounding board — her validation, her comfort, her constant attention — with zero physical or romantic reciprocity (回報). She gets all the gain, and you get emotionally drained. This is not a true friendship; it is a parasitic dynamic you trained her to expect. She knows you will always answer, always listen, and, most crucially, always stay.
The Flip: Remove Access
You remove the access she has come to expect.
This isn’t done to punish her; it’s done to reset the entire dynamic (互動關係). When she feels your total absence, her body reads it as an immediate loss (身受失落之苦). Loss is the trigger for evaluation. She will either upgrade the way she treats you and the position you hold, or she will disappear completely, confirming your position was simply a placeholder.
The outcome is a 100% win for you, because the man who strategically withdraws his attention from manipulation always comes back stronger and of higher value.
4.“We’ll hang out soon.”
“Soon” sounds like interest, but it’s actually a perfected mechanism of avoidance (躲掉/避開奧步). It’s her way of keeping you emotionally attached to a future that never, ever arrives.
“We’ll hang out soon,” “I’ll text you soon,” “I’ll be ready soon.” She is pacifying you. This is a tactic of temporal delay reinforcement — promising a future reward so you ignore the present neglect. Most men fall for it because hope feels productive.
But hope without proof is a trap. If a woman genuinely wants to see you, there is no “soon.” There is a plan.
When she defaults to that word, you must step back instantly and draw a clear boundary. Boundaries reveal truth far faster than words ever can.
The Flip: Demand the Plan
When she realizes she can’t delay you into submission, she is left with only two choices:
step up and define a concrete plan, or
disappear.
Both outcomes instantly expose her true intentions, and once you have clarity, you stop being confused.
The Final Shift to Control
Women don’t reveal their true motives in long, dramatic paragraphs. They reveal them in these single words: busy, maybe, friend, soon.
These aren’t casual phrases. They are indicators of leverage. Each one tells you exactly where she believes your value stands in her priorities.
The man who reacts to them loses ground. The man who observes, adjusts, and maintains his composure gains it. A woman doesn’t respect the man who chases clarity; she respects the man who already possesses it because he values himself enough to not tolerate uncertainty.
Power is not in what you say back. It is in what you no longer feel you have to respond to.
When you stop reacting to weak, mediocre language and start holding the line on your own value, she is the one who starts adjusting to you. That’s the moment uncertainty turns into a genuine pursuit.
Share your thoughts in comments; we respect your opinion.
Written by The Female Code
Exploring the heart of human connection—writing about love, trust, and the art of building meaningful relationships.
Published in Write Your World
“Write Your World” is a space for storytellers, thinkers, and creatives to share their personal journeys, ideas, and experiences. Here, we believe words have the power to shape reality; join us as we explore life through storytelling.
相關閱讀
She Was Into You — Until You Did This One Silent Thing That Killed Her Desire
If She Does These Things… She’s Secretly Flirting With You.
本文於 修改第 2 次
|
|
「字」從那裏來？ ---- Ingrid Schou
|
|
|
推薦1 |
|
|
|
How did the first words originate?
The first words may have emerged 135,000 years ago.
What could these guys have been saying to each other? Well, that's hard to say. (Illustration: Fractal Pictures / Shutterstock / NTB) 請至原網頁觀看示意圖
Ingrid Schou, journalist, 11/28/25
If you slide your tongue along your teeth all the way back, you’ll find your molars.
“Jeksel” – the Norwegian word for molar – “is a strange word,” my colleague said.
“Yes,” I agreed. "Let's find out where it comes from.”
According to the Norwegian dictionary, jeksel derives from the Old Norse word jaxl. And that's where the explanation ends.
But what kind of word is jaxl? And how did words emerge, way back in the beginning?
Probably started as sounds
“In short – we don't know,” says Sverre Stausland. He is a professor of linguistics at the University of Oslo.
“The first words and languages haven’t left any traces,” says Jan Terje Faarlund, also a linguistics professor at the University of Oslo.
Part of the reason is that words arose so long ago – well before humans learned to write and longer still before any audio recorders were available. The latest research suggests that verbal languages may have arisen 135,000 years ago.
Ugh! Ouch! Oh!
Our human species, Homo sapiens, has existed for around 300,000 years. At least that is what we have solid evidence for to date. Some researchers believe that we may yet find even older skulls and skeletal remains of our species.
But regardless, we might have lived without words for more than half of our time as Homo sapiens. That seems almost impossible – but remember that no other species besides ours uses words today either. Nor do dogs or elephants speak with words.
“It could be that we used body language,” says Faarlund.
Like pointing at things, hugging to show love, or touching our stomachs when we were hungry.
“Early humans probably made sounds to express emotions like joy, fear and pain. And then they probably had other sounds to warn of danger, call to each other and so on.
Just think of sounds like ugh, ouch, or oh.
“Are they really ‘words’ as such?” asks Stausland.
From sounds to words
Researchers believe that the first proper words most likely originated from imitation.
“People would try to imitate the sound that some animal or thing made,” says Faarlund.
An example is the ancient Egyptian and Chinese word for cat – “mao,” which is similar to the “meow” sound that cats make.
“How the rest of our words originated is a big mystery,” says Faarlund.
And the same applies to the word for the tooth at the back of the mouth. Jeksel remains a mystery.
“We don’t know where the word comes from,” Stausland says.
Words have both a function and a history, but basically they often consist of random sounds.
“Words are really just sounds that allow us to distinguish them from each other,” says Stausland.
Today, we often use words we already have in our vocabulary to create new ones. Just think of ‘snowboard’ or ‘cellphone’, for example, or the word Lego which is made up of the Danish words leg godt, meaning ‘play well’.
"Mamama, papapa"
So we don't know what the very first word is. But researchers have tried to find some of the oldest words that still exist. They include "mama" and "papa".
“These words are found across many languages in the world,” says Stausland. “It's easy to understand why. Small babies make their first sounds with their lips,” he says.
Those sounds correspond to the letters m, p and b, and the vowel a. That's why the first sounds are often "mamama" and "papapa".
“When the mother or father is nearby, they think the child is using a word about them. But these are actually just the simplest sounds a baby can make,” says Stausland.
Language on the move
Our species originated in Africa, and gradually humans spread across the globe. We brought with us the ability to learn languages, and today we have between 6,000 and 7,500 different languages, according to SNL.no.
People with different languages met long before there were schools, language books or Google Translate. For example, the Vikings travelled a lot. How did they manage to talk to people? You can read more about that here.
Perhaps people in the future will also wonder about what words and languages people used before them. This research will continue to be a difficult task, because languages come and go.
UNESCO believes that 1,500 of today's languages are at risk of disappearing. You can read more about that here.
References:
First traces of language: Miyagawa et al. (2025). Linguistic capacity was present in the Homo sapiens population 135 thousand years ago. Frontiers in Psychology, 16. DOI: https://doi.org/10.3389/fpsyg.2025.1503900
First Homo sapiens discovery: Hublin, J.-J. etc. (2017). New fossils from Jebel Irhoud, Morocco and the pan-African origin of Homo sapiens. Nature, 546, 289–292. https://doi.org/10.1038/nature22336
Translated by Ingrid P. Nuse
Read the Norwegian version of this article at forskning.no
本文於 修改第 1 次
|
|
考古學家發現未知文字 -- Tim Newcomb
|
|
|
推薦1 |
|
|
|
Archaeologists Found an Ancient Tablet With 39 Letters That Don’t Belong to Any Known Language
Google Translate isn’t going to help here.
Tim Newcomb, 11/22/25
These Letters Don’t Belong to Any Known Language Dorling Kindersley - Getty Images 請至原網頁觀看新發現未知文字的照片
Here’s what you’ll learn when you read this story:
* Archaeologists uncovered a basalt tablet in the Bashplemi Lake region of Georgia with an unknown language carved into its face.
* The tablet featured 60 characters across seven rows.
* Experts said that the etchings showed excellent craftsmanship, even if they can’t yet determine the language’s origin.
There’s a new language in town. Well, actually, it’s ancient, and experts can’t even read it yet. But they’re excited to find out more.
Archaeologists discovered a basalt tablet about the size of a piece of paper bearing 60 unknown script characters expertly etched onto its surface in the Bashplemi Lake region of Georgia—the same site where some scientists believe the first European, a 1.8-million-year-old hominin, was discovered.
According to a study published in the Journal of Ancient History and Archaeology, the tablet—which measured 9.4 inches by 7.9 inches—was made from local vesicular basalt and featured seven rows of writing.
“This tablet, which bears 60 signs, 39 of them different, raises the question of the origin of the Georgian script, proto-Georgian,” the study authors wrote. “While the basalt on which it is based is known to be of local origin, its meaning is unknown, and there remains a long way to go to decipher it.”
An initial comparative analysis conducted with over 20 languages shows that the characters bear some similarities with the written forms of the Semitic, Brahmani, and North Iberian languages.
“Generally, the Bashplemi inscription does not repeat any script known to us,” the authors wrote, “however, most of the symbols used therein resemble ones found in the script of the Middle East, as well as those of geographically remote countries such as India, Egypt, and West Iberia.”
Some symbols may have taken inspiration from early Caucasian scripts—whether that be Georgian Mrglovani or Albanian alphabets—but there also seem to be ties to Proto-Kartvelian, Near East Phoenician, Proto-Sinaitic scripts. But without a direct link to any other known pattern of writing, this new find could be a completely unknown language.
“The script, some of whose 39 characters are numbers and punctuation marks, may have been an alphabet,” the authors wrote.
Researchers believe that the new find bears the strongest resemblances to the Proto-Kartvelian script from the fourth millennium B.C., which was used throughout Georgia and Iberia. But there are also likenesses to Bronze Age Georgian symbols, including “some similarities with Phoenician, Aramaic, and Greek alphabets [that] are not surprising as their role in the region and their relations to local scripts are well-known.”
The area in which this tablet was found is already an archaeologically rich location, and adding a new language to the mix only furthers the intrigue of Bashplemi Lake.
The 60 total characters etched across seven horizontal rows also showed off intensely skilled craftsmanship, according to the study, and would have been done with advanced tools for the time. Researchers believe the person who crafted the writing used a conic drill to outline the contours of each individual character and a “smooth and round-head tool” to finish the job.
Speculation on what it all means—the authors hypothesize that the writing could explain “military spoils, an important construction project, or an offering to a deity”—is all anyone has to go on for now.
本文於 修改第 1 次
|
|
|
本城市首頁
看回應文章
等級：8
