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Record W2102055183 · doi:10.1177/0192513x08329293

Making Space for Graduate Student Parents

2008· article· en· W2102055183 on OpenAlexaff
Kristen W. Springer, Brenda Parker, Catherine Leviten‐Reid

Bibliographic record

VenueJournal of Family Issues · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGraduate studentsPresentation (obstetrics)Graduate educationMedical educationWork (physics)Space (punctuation)PsychologySociologyPedagogyMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex

Work—family issues of graduate students are nearly invisible, despite record numbers of men and women in graduate school during their peak childbearing years. Furthermore, very little is known about what, if any, services are available for graduate student parents. In this article we describe the theoretical and practical tensions between society's view of idealized mothering and academia's vision of graduate students as idealized workers. We then present results of a survey about parental supports for graduate students administered to graduate directors of sociology PhD programs. The results demonstrate that few official policies exist, most situations are accommodated individually, and graduate directors are often unaware of university services for graduate student parents. The article concludes with a detailed presentation of potential departmental and university initiatives designed to support graduate student parents. These initiatives can be readily incorporated by graduate departments and universities to help curb the leaking pipeline of women in academia.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.003
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.003

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.

Opus teacher head0.238
GPT teacher head0.441
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations168
Published2008
Admission routes1
Has abstractyes

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