Bibliographic record
Abstract
Abstract: Team reasoning is thought to be descriptively and normatively superior to the classical individualistic theory of rational choice primarily because it can recommend coordination on Hi in the Hi-Lo game and cooperation in Prisoner's Dilemma-type situations. However, left unanswered is whether it is rational for individuals to become team members, leaving a gap between reasons for individuals and reasons for team members. In what follows, I take up Susan Hurley's attempt to show that it is rational for an individual to become a team member. I argue that her account fails to show that becoming a team member is necessary to gain the advantages of coordination in Hi-Lo games or cooperation in Prisoner's Dilemma-type situations, and that individuals will often fare better reasoning as individual agents than as members of a team. I argue further that there is a more general problem for team reasoning, specifically that the conditions needed to make it rational for a team member to employ team reasoning make becoming a team member unnecessary.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".