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Record W7132910662

Work-life Balance among Female Dentists In Canada

2020· dissertation· W7132910662 on OpenAlexaboutno aff
Doreh Behzadpoor

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsWork–life balanceBalance (ability)BurnoutPersonal lifeSample (material)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

Work-life balance is increasingly gaining attention as a possible predictive factor in emotional exhaustion and burnout among professionals. While there are studies that point to challenges to work-life balance among female dentists in the United States, there is no study that looks into these issues in Canada, nor has the specific nature of these issues among female dentists been documented anywhere. The first part of our study consisted of secondary statistical analysis of previously collected survey data from a random sample of 3000 dentists practicing in Ontario in 2012 showing significant gender differences, such that female dentists appear to face more obstacles to a well-balanced work and life. In the second part, a qualitative study into what and how female dentists encounter challenges to work-life balance showed nature of the profession of dentistry, dental practice structure, personal life factors, and personal attributes to be contributing factors to such challenges.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.039
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.063
GPT teacher head0.435
Teacher spread0.372 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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