A Dogma Not Worth Exhuming: Empiricism in Language, Intelligence, and Thought
Bibliographic record
Abstract
I will demonstrate that a central presupposition of Barrow's Language, Intelligence, and Thought (1993) is the empiricist dogma that there is ''some fundamental cleavage between truths which are analytic, or grounded in meanings independently of matters of fact, and truths which are synthetic, or grounded in fact" (Quine, 1953, p. 20).The analytic/synthetic distinction survived after Quine's revolutionary work only as a pragmatic tool for distinguishing language users' intentions in given contexts.However, in Barrow's recent book, the intrinsic, fundamental distinction as found in logical empiricism has been exhumed.Reliance on the dogma, I contend, threatens the positive aspects of many of Barrow's ideas.The role for philosophy of education in scholarly research on intelligence, which Barrow wishes to articulate, cannot be founded on an unsound philosophical theory.The empiricist dogma that the analytic and synthetic differ fundamentally is not worth exhuming.I will give a very brief overview of the main points of Barrow's thesis, and mention several caveats about the overall agenda, though the latter will not be pursued in depth.Thence, I will turn to the main task of showing how the empiricist version of the analytic/synthetic distinction is presupposed in much of Barrow's argument.Finally, I will provide a brief sketch of how to study language, intelligence, and thought without the empiricist dogma. An Overview with CaveatsI take Barrow's main points to be these four: (a) we should conceive of education as the development of understanding; (b) understanding comes in
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.051 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".