Strange Bedfellows: Conservative Governments and Family Policy in Canada and Germany, 2005 - 2015
Bibliographic record
Abstract
This dissertation contributes to the academic literature on recent and ongoing family policy reforms in affluent countries by comparing the respective family policy agendas of right party led governments in Canada and Germany between 2005 and 2015. My comparative assessment of reforms enacted by the governments of Stephen Harper and Angela Merkel, respectively, indicates that an increased cross-national salience of the financial and logistical challenges faced by modern (dual-earner) families presents right-of-center parties with an incentive to utilize family policy proposals instrumentally to broaden their electoral appeal. This gives vital context to large-n statistical research that indicates a weakening of partisanship as an explanatory variable for recent family policy developments. The study also finds that differences in the specific policies implemented by each government can ultimately be traced back to the domestic discursive context. Germany presented the more favorable environment for comprehensive, women’s employment supporting reforms due to a widespread perception of the low domestic birth rate as a threat to intergenerational ‘sustainability’. The cause was also helped by the presence of credible policy spokeswoman Ursula von der Leyen, who championed a progressive package of reforms while, at the same time, embodying a traditional image of maternity that appealed to conservatives. By contrast, the Canadian political environment favored a continuation of direct cash payments to families, as exemplified by the Harper government’s signature Universal Child Care Benefit (UCCB). Harper later launched two children’s activity tax credits crafted to appeal to families in critical suburban ‘swing ridings’. Although both opposition parties proposed a national daycare strategy as an alternative to Harper’s agenda, the idea has only limited popular appeal due to the questionable record of the country’s only standalone provincial daycare program, based in Québec, and a silencing of feminist perspectives in the national policy dialogue. Lastly, I find that an ancillary discourse linking family policy to the cultural integration of migrants was visible in Germany but not in Canada. This finding is substantiated in Chapter 5 via a statistical topic analysis of over 450 relevant newspaper articles. I also draw from 25 personal interviews in my discussion of Canada.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".