Promouvoir les comportements pro-environnementaux grâce à l’hypocrisie induite
Bibliographic record
Abstract
Dans le domaine de la consommation pro-environnementale, les recherches se sont évertuées ces dernières années à expliquer l’écart existant entre les attitudes et les comportements effectifs. Trois études expérimentales montrent que lorsque la contradiction entre ce que les individus disent et ce qu’ils font est rendue saillante, c’est-à-dire dans une situation d’hypocrisie induite, ils réduisent de manière indirecte la dissonance cognitive qui en résulte en étant plus altruistes à l’égard d’associations qui agissent pour l’environnement mais pas pour des associations humanitaires. Cet effet de l’hypocrisie induite n’est plus significatif lorsque les individus ont pu, au préalable, affirmer leur Soi.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.005 |
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; both teacher heads agree on what is shown here.
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".