Notice bibliographique
Résumé
Throughout most of its history, higher education has been the exclusive domain of men. Women and other historically underrepresented groups, such as persons with disabilities, racialized people, and gender and sexual minorities, have made inroads into academia only in the last century. Still, higher education structures—built around affluent, able-bodied, heterosexual cisgender men—continue to create barriers for participants who do not fall within those narrow identity dimensions. Even though women and gender-diverse individuals have made immense progress in carving out their place in the academy—women constitute the majority of college students in many countries—challenges remain in reaching parity. Women’s concentration in lower faculty and management positions and overrepresentation in fields with limited financial rewards, such as arts and humanities—as science, technology, engineering, and mathematics (STEM) fields continue to be chilly to women—is quite troubling. Trans individuals and people with nonbinary gender identities also face massive obstacles to participation and advancement in academia. Obstacles to participation are further compounded for people with intersectional marginalized identities. Top leadership at universities remains dominated by mostly cisgender male, white, and affluent individuals, while inclusion of the full spectrum of gender identities in data collection has only begun recently and remains scarce and uneven across institutions. The sole focus on cisgender women when considering gender in higher education has (rightly) become obsolete. However, since cisgender women outnumber men in most areas of higher education, arguments are made that systemic barriers for women are no longer an issue in higher education. A majority of contemporary feminist scholars push back on this argument while continuing to expand the notion of gender itself to be more inclusive and paying particular attention to intersectionalities of gender identities. Diversity, equity, and inclusion efforts in some Western universities have contributed to making the academy more democratic and inclusive of historically marginalized identities, however a critical examination of gender in higher education indicates that much remains to be done. Since the author received her doctorate in the United States and is employed at a university in Canada, this bibliographic collection is skewed in favor of resources originating from and focusing on gender and higher education in the United States; however, the author has taken care to include influential cross-national works available in the English language. For the purpose of this collection, the term “critical” is firmly grounded in critical race theory and critical feminist perspectives (again with origins in primarily North American scholarship) that posit that higher education structures are inherently racist and gendered, to underscore higher education’s contested relationship with gender and resistance to gender equality. Hence, works included in this bibliography provide a critical examination of the historical and current challenges for an in-depth understanding of the origins and status of gender disparity in higher education.
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 | 0,017 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,016 | 0,097 |
| Communication savante | 0,015 | 0,020 |
| Science ouverte | 0,003 | 0,010 |
| Intégrité de la recherche | 0,008 | 0,014 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».