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Record W4200166246 · doi:10.47678/cjhe.v51i4.188917

Achieving academic promotion: The role of work environment, role conflict, and life balance

2021· article· en· W4200166246 on OpenAlexaffvenueabout
Elizabeth Bowering, Maureen J. Reed

Bibliographic record

VenueCanadian Journal of Higher Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsToronto Metropolitan UniversityMount Saint Vincent University
Fundersnot available
KeywordsPromotion (chess)ConformityWork (physics)ProductivityPublic relationsPsychologyBalance (ability)Value (mathematics)SociologySocial psychologyMedical educationPolitical scienceMedicineEconomic growth

Abstract

fetched live from OpenAlex

Fifty-two faculty at two Canadian universities were interviewed about the impact of work environment, role conflict, and worklife balance on career-related experiences and decisions to apply for promotion to full professor. Faculty described conflicts between their academic responsibilities of teaching, research, and service (including limited time for research despite long work weeks) as well as work-life imbalance. These issues were often gendered; women took slightly longer to achieve the rank of associate professor, accepted tasks of lower reward value, held decreased expectations for promotion, and experienced workplace conflict and bullying more than their male counterparts. Even so, faculty identified colleagues as a valuable career support. Our data lead us to theorize that the decision to apply for academic promotion is informed by a cost-benefit analysis, early career experiences, conformity with academic norms that over-emphasize research productivity, as well as access to career-advancing resources (especially time for research). We recommend that the gendered nature of the academic reward system be re-imagined to promote equality, and provide suggestions as to how to do so.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.054
GPT teacher head0.280
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2021
Admission routes3
Has abstractyes

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