The rationality debate as a progressive research program
Bibliographic record
Abstract
Abstract: We did not, as Brakel & Shevrin imply, intend to classify either System 1 or System 2 as rational or irrational. Instrumental rationality is assessed at the organismic level, not at the subpersonal level. Thus, neither System 1 nor System 2 are themselves inherently rational or irrational. Also, that genetic fitness and instrumental rationality are not to be equated was a major theme in our target article. We disagree with Bringsjord & Yang's point that the tasks used in the heuristics and biases literature are easy. Bringsjord & Yang too readily conflate the ability to utilize a principle of rational choice with the disposition to do so. Thus, they undervalue tasks in the cognitive science literature that compellingly reveal difficulties with the latter. We agree with Newton & Roberts that models at the algorithmic level of analysis are crucial, but we disagree with their implication that attention to issues of rationality at the intentional level of analysis impedes work at the algorithmic level of analysis.
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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 | 0.042 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.058 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.008 | 0.014 |
| 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".