Canadian researchers advise law firms to ensure employees feel empowered to negotiate work-life balance (WLB)
Bibliographic record
Abstract
Purpose The purpose was to find out how lawyers at high-profile legal firms managed WLB. Design/methodology/approach The researchers conducted interviews with 42 lawyers at two law firms in a large West Coast city. Both participating law firms focus on corporate law and employ around 100 lawyers. Interviews took place on site over a three-month period. They lasted between 20 minutes and an hour. Questions covered general experience in the profession, as well as balancing work and non-work lives. Findings The answers revealed the tensions between work and non-work experiences. Lawyers were driven to work long hours and expected to respond quickly to clients’ needs. But they had diverse attitudes to WLB. They could broadly be divided into three categories – “work-centric,” “non-work centric,” and “dual-centric.” Their life values were also strongly correlated with gender. Only dual-centric and life-centric female lawyers had actively negotiated alternative work arrangements Originality/value There has been very little qualitative research into workplace attitudes to WLB
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.033 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.003 |
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.
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".