The use of mobile technologies for work-to-family boundary permeability: The case of Finnish and Canadian male lawyers
Bibliographic record
Abstract
This article explores work–family interface and the use of mobile technologies (MTs) among male lawyers in Quebec (French Canada) and Finland – two civil law contexts with reputations for legislation friendly toward work–family balance. Drawing on 34 interviews with male lawyers and combining two theoretical lenses, shifting ideals of fatherhood and work–family boundary theory, our study shows how men’s preferences for work–family boundary management relate to diversifying models of fatherhood and family. In Finland, male lawyers more readily embrace family responsibilities and they strive to set firm boundaries to curtail work spilling over into family life. Yet, the cultural and professional norm of men as breadwinners remains strong, especially for Canadian male lawyers whose spouses more often assume primary responsibility for childcare. Our study offers qualitative markers of boundary management styles and strategies (spatial, temporal, and psychological) of male professionals – as struggling segmentors, struggling integrators, and integrators. We observe that senior male lawyers, living in more traditional family models, frequently model integrating behaviours, such as around-the-clock availability via MTs. This modeling establishes expectations of what represents a committed professional worthy of promotion. These practices play an important role in sustaining and reproducing gender inequalities in organisations that employ professionals.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".