The evolution of preferences and competition: a rationalization of Veblen's theory of invidious comparisons
Bibliographic record
Abstract
Abstract. We examine how preferences evolve by natural selection in a competitive environment similar to that characterizing much of our evolutionary past. We find that the evolutionarily stable preferences in this context exhibit a concern not only for absolute payoffs but also for relative payoffs, and that this intensifies the degree of competition relative to what obtains when players consider only absolute payoffs. We argue that this has consequences for the equilibrium population size. We argue that the premise of this analysis is consistent with the available anthropological evidence, and that the prediction is broadly consistent with the findings of experimental game theory. JEL Classification: C70 Evolution des préférences et concurrence: une rationalisation de la théorie des comparaisons désobligeantes de Veblen. Les auteurs examinent comment les préférences évoluent par sélection naturelle dans un environnement concurrentiel qui ressemble à celui qui a caractérisé notre passéévolutionnaire, c’est‐à‐dire, un environnement de chasseurs et de cueilleurs. On découvre que les préférences évolutionnairement stables dans ce contexte révèlent un intérêt non seulement pour les résultats en termes absolus mais aussi pour les résultats en termes relatifs, et que cela intensifie le degré de concurrence par rapport à ce qui se passerait si les joueurs prenaient en compte seulement les résultats en termes absolus. En travaillant contre l’espèce si l’on peut dire, la sélection naturelle des préférences réduit les niveaux d’équilibre des populations en deçà de ce qui aurait prévalu si les préférences n’avaient pas évolué. Le postulat de base sur lequel cette analyse se fonde est compatible avec les résultats des travaux anthropologiques et les prédictions sont compatibles avec les résultats des travaux en théorie des jeux expérimentale.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".