Differential Relationships Between Work-Life Interface Constructs and Intention to Stay in or Leave the Profession: Evidence From Midwives in Canada
Bibliographic record
Abstract
This paper investigates how positive and negative work-personal life interface constructs are differentially associated with intentions to stay in or leave the profession. The findings help map work-personal life interface constructs on the typology of determinants of intention to stay and intention to leave (disengagers, retainers, criticals, and neutrals). The ordered logistic regression (ologit) modelling of cross-sectional data from a representative sample ( n = 601) of midwives in Canada shows that work interference with personal life is a disengager, which has a stronger association with intention to leave than with intention to stay in the profession. Among the work-personal life interface constructs, work enhancement of personal life seems to be the most critical determinant, showing the most substantive association with both intention to stay and intention to leave. This finding suggests that interventions to increase midwives’ intention to stay and decrease their intention to leave should focus on amplifying the enhancing effects of working on midwives’ personal lives. Interventions that aim to reduce work interference with personal life might be more effective in decreasing intention to leave the profession than increasing intention to stay.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".