L’empathie comme variable médiatrice de persuasion: le cas des campagnes sociales antidiscrimination
Bibliographic record
Abstract
Les interventions publicitaires constituent des activites fort complexes qui necessitent que les facteurs qui sont susceptibles d’optimiser leur efficacite soient clairement identifies. Dans le cadre des campagnes antidiscrimination, et ce, puisque les attitudes envers l’exogroupe sont notoirement difficiles a changer, il est d’autant plus pertinent de choisir les strategies qui permettront d’eviter les effets boomerang ou d’autres mecanismes de resistance a la persuasion. Eu egard aux interventions visant a ameliorer les relations intergroupes, plusieurs chercheurs ont conclu a la pertinence de l’empathie pour attenuer les prejuges et minimiser les chances que les comportements discriminatoires se produisent. Cet article discute de l’importance des interventions publicitaires se basant sur l’empathie dans la lutte contre la discrimination et du role de l’empathie comme variable d’influence du processus persuasif. Media interventions are complex activities and thus require that the elements susceptible to enhance their efficacy be promptly identified. In regard to interventions aiming to improve intergroup relations, several researchers have found empathy to reduce prejudice and to have an overall positive effect on intergroup attitudes. Since attitudes towards the out-groups are notoriously hard to change choosing a strategy that will avoid boomerang effects or other mechanisms of resistance to persuasion is of outmost importance. This article discusses the importance of empathy-based interventions in tackling discrimination and the role of empathy in the persuasion process.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".