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Enregistrement W3111826397 · doi:10.15695/amqst.v10i1.3813

Maureen Baker, Academic Careers and the Gender Gap

2013· article· en· W3111826397 sur OpenAlexaboutno aff
Caroline Farrior Boone

Notice bibliographique

RevueAmeriQuests · 2013
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueDiversity and Career in Medicine
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGender gapPolitical scienceSociologyPsychologyGender studiesDemographic economicsEconomics

Résumé

récupéré en direct d'OpenAlex

In Academic Careers and the Gender Gap, Baker demonstrates how the gender gap and university institutions have changed simultaneously over time and offers an explanation as to why the gender gap persists in liberal states despite numerous economical, social, and institutional advances that have been made: "The gender gap has been diminishing for decades, yet it is nonetheless perpetuated by institutional priorities, academic practices, collegial relations, variations in family circumstances, and gendered priorities," Baker writes (173).The first study, which she undertook in 1978, dealt with women employed at University of Alberta in western Canada (175).The following two studies, each conducted in 2008 at two different universities in New Zealand, focused on comparing responses from both men and women (175).In an effort to situate her findings in a global context, Baker complements her own research with results and statistics from studies done in the following liberal states: the United States, the United Kingdom, and Australia (17).Baker cautions the reader however that her studies are not meant to provide "a systematic comparison" of the gender gap in either country, but rather to promote "a fuller understanding of the personal experiences and perceptions of individual academics" (175).With 38 years of experience in the academic field at the time of her book's publication, Baker is no doubt well-qualified in and knowledgeable of her chosen area of study on both a practical and a theoretical level (21).Having taught and researched at the university-level in five different liberal states, Baker no doubt has an insider's perspective on the glass-ceiling predicament and knows the long hours and hard work involved in obtaining and maintaining a successful academic career (21).Furthermore, Baker uses feminist political economy theories, social capital theories, and interpretive frameworks as lenses through which to examine the gender gap.She also considers how 'the motherhood penalty,' as well the domestic division of labor, effect women's experiences in academia.Overall, Baker's study is organized and presented well.Baker initiates each chapter with colorful, verbatim quotes taken from interviews she conducted."[My parents] thought that after I got my PhD I would settle down and be 'normal'. . .They brag about what I have done, but they think I'm a deviant," reads one quotation from a part-time Canadian lecturer in 1973 (26).Before launching into new material in each chapter, Baker quickly and briefly reviews findings from previous chapters and finishes each chapter with well-written conclusions.Though these recapitulations seem repetitive at times, they ultimately help keep the reader on track and prevent him or her from getting lost in the large amounts of data that are presented.Furthermore, Baker divides her chapters into themed sections, which are then separated into subsections by the year in which studies were conducted.For example, Baker divides her chapter entitled "Social Capital and Gendered Responses to University Practices," into sections discussing job qualifications, mentoring trends, hiring practices, and even institutional support programs.For each of these topics, Baker presents data that is clearly delineated by year, thereby making continuities or differences easier to spot.Though Baker's work is well researched and well documented, as evidenced by her extensive list of references, her study does harbor some limitations of which the reader should be aware.Her studies each consisted of relatively small samples and were not selected at random, two characteristics that prevent us from drawing any general conclusions from her work.Baker herself acknowledges this disadvantage (180).Furthermore, Baker acknowledges that the differences among teaching and research universities are "blurred" as more academics at each type of institution are pressured to produce more research (7).Additional studies with a focus on smaller liberal arts colleges might be an interesting expansion on her existing study.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,009
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0110,020
Communication savante0,0080,015
Science ouverte0,0020,005
Intégrité de la recherche0,0060,009
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,037
Tête enseignante GPT0,306
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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