Bibliographic record
Abstract
Social constructivism about races holds that races are socially real, that is, they are identical with socially constructed properties, or social kinds.one particular version of social constructivism, namely, historical constructivism, claims that the properties that make a group of people a race are certain historical properties of the individuals that belong to that group (e.g., the life histories of the members of the group, or their ancestors).Joshua Glasgow has recently argued, following appiah, Gooding-Williams and others, that historical constructivism faces several problems.In particular, he argues, it faces a trilemma: either the characterization of races provided is circular, or, if it wants to avoid circularity, it will turn out to be either redundant or indeterminate.In this paper, my main aim is to explore this interesting challenge to historical constructivism about races, and argue that it can escape Glasgow's trilemma.I will focus on historical constructivism about races, but I hope my discussion will shed some light on the question of whether social constructivist accounts in general are tenable.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.064 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".