Bibliographic record
Abstract
The study of linguistic metatheory is an essential part of the linguist's development and so should figure in the training that is required of all students in the field.However, it is not at present accorded even a small part of this importance.The development of knowledgeable, critical linguists is a goal to which all of us ascribe as teachers of 1 inguistics.A 'knowledgeable' 1 inguist would be one fami 1 iar with different theories, hypotheses, opinions and how to perform the analysis of data they advocate.We take this to be the responsibility of the di sci pl ines of linguistic theory: phonology, morphology, syntax, semantics, pragmatics.A 'critical' 1 inguist would be one with the capacity for critical thinking and expression, i.e. critical evaluation and use of his knowledge; this is the responsibility of the discipline(s) of linguistic metatheory.Combining aspects of the Theory Comparison Method that Dougherty (in Botha 1979:240) advocates with the 'valuing skills' of Raths, Harmin and Simon (1966, Chapt.3), Bunge's (1967,1 :9) stages of the scientific method, and the 1 iterature on critical and scientific thinking as synthesized by Ennis (1962), we can suggest Ten Criteria for Critical Science (C-criteria) (see FIGURE 1, fol lowing page), They summarize the skills necessary for a critical approach to science and thus make our notion of 'critical' more precise.Linguistic metatheory, a specific branch of metascience (see Bunge 1959), .isnecessary because it defines and examines these criteria and provides the tools for complying with them.11, We need to be more precise about what we mean by LINGUISTIC METATHEORY so as to make its role in developing critical linguists clearer.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".