Bibliographic record
Abstract
Abstract Does your language distinguish between dark and light blues? Do your verbs require a report on where and how you got your information? Can you easily talk about non-actual situations in your language? What does this mean for the way you see the world, if anything? Linguistic relativity, also known as Whorfianism by some, is actually a group of related positions that postulate that one’s native language generates some set of important directions or limitations on one’s cognition. In its extreme form, it even suggests that languages can create distinct (and possibly incompatible) worldviews. Recent cross-linguistic experiments on subtle grammatical distinctions between colour words or the presence of subjunctive conditionals have reignited the once furious debate on just how much our languages can shape the way we see the world. This book traces the development of the concept of linguistic relativity through the centuries, paying particular attention to Benjamin Whorf and the evidence for or against the various claims he made in this realm. We follow that with the application of linguistic relativity to modern attempts to verify it, as well as to certain social and intellectual endeavours that are prominent in the current philosophic, linguistic, and cognitive science literature.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".