Bibliographic record
Abstract
In the recent twenty-year retrospective issue of Animal Behavior and Cognition, Povinelli and Henley (2020) argue that a host of comparative studies into “complex cognition” suffer, fatally, from a theoretical confusion. To rectify the problem, they issue the following challenge: alongside specifications of the higher-order capacity to be tested, provide hypotheses of the mechanism(s) necessary to implement it. They spearhead this effort with a discussion of how the Relational Reinterpretation Hypothesis (RRH) provides just such an account. In the first part of the paper, I argue that RRH is neither necessary nor sufficient to explain the second-order behavior in question. In part two, I describe an alternative hypothesis, externalism, that does sufficiently account for it. Further, it opens new avenues of comparative research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.005 | 0.017 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.024 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".