The Effect of Gender Stereotypes on Perceived Decision Making Abilities
Notice bibliographique
Résumé
The purpose of this study was to explore and study the effects of both positive and negative stereotypes on the perceived decision making abilities of those exposed to them. Past research has indicated that prejudice towards women exists more prevalently and more intensely in society than it does for males. Accordingly, we predicted that women would respond more negatively to such stereotypes than men would when presented with them. We then measured this by asking participants to judge their perceived agency in hypothetical situations that required decision making. We tested this with both positive and negative stereotypes, and also with a control. Our findings did produce significant results showing a main effect of participant gender (female) causing them to rate themselves more negatively then males on average. These results are important because they show that women respond negatively to these pervasive and flawed stereotypes attributed to their gender which could negatively affect their ability to make efficient decisions in everyday life. the effect of Gender stereotypes on perceived decision MAkinG Abilities This study was conducted to find out if stereotypes have an effect on peoples’ perceptions of their own ability to make decisions. This relies on these stereotypes existing pervasively in our society, and also that people (specifically women) are aware of them on at least some level of consciousness. Past research has studied and shown evidence that these stereotypes do in fact pervade throughout society: “Also, social scientists are in general agreement that women face discrimination in many occupations...”1 ...and are also perceived, both consciously and subconsciously, by both women and men: “Moreover, women themselves, although not necessarily believing themselves personally deprived, do perceive that women as a group are unjustly treated.”2,3 “...therefore, anti-female bias, often functioning out of people’s conscious awareness...”4 The fact that these stereotypes exist in society, enough to warrant recognition by many organizations and interest groups raises the question of how they might affect those they are directed towards. From this past research and the questions that followed, we extrapolated that these stereotypes could be having profound effects on both the men and women that they targeted. Specifically, we wanted to know how they may affect the way a person regards their ability to make decisions when presented with hypothetical scenarios. Thusly, we hypothesized that gender stereotypes could ultimately affect a person’s perceived decision making abilities concerning future events We expected to find that when presented with positive stereotypes, participants would perceive themselves as 1 Eagly, A. H., & Mladinic, A. (1994). Are people prejudiced against women? Some answers from research on attitudes, gender stereotypes, and judgments of competence. European Review of Social Psychology, 5, 1-35. 2 Crosby, F. (1982). Relative Deprivation and Working Women. New York: Oxford University Press. 3 Major, B. (1989). Gender differences in comparisons and entitlement: Implications for comparable worth. Journal of Social Issues, 45(4), 99-115. 4 Banaji, M. R., & Greenwald, A. G. (1994). Implicit stereotyping and prejudice. In M.P. Zanna & J. M. Olson (Eds). The Psychology of Prejudice: The Ontario symposium (Vol. 7, pp. 55-76). Hillsdale, NJ Erlbaum.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».