Balancing Family and Work: Challenges Facing Canadian MPs
Bibliographic record
Abstract
Many Canadians struggle to balance their families and careers. A 2011 Harris/Decima poll, reports that 47% of Canadians struggle to achieve a work-life balance, and family is often an important aspect of that balance. Certain professions, including that of MP, make achieving such a balance more difficult than others. This article looks at the overall nature of the strain on MPs the two strategies that MPs employ to adapt the challenges of the job, and potential reforms that might work to assuage some of the strain placed on MPs and their families. The data for this paper comes from a series of semi-structured interviews conducted by Samara, an independent charitable organization that improves political and democratic participation in Canada, as part of its MP Exit Interview Project. This paper used transcripts from the interviews of 65 former MPs who left public life during or after the 38th and 39th Parliaments. These men and women served, on average, 10.5 years, and together represented all political parties and regions of the country. The group included 21 cabinet ministers and one prime minister.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".