The Marginalization of Canadian Civil Society Organizations and the Challenges of Promoting Gender Equality under the Harper Conservatives (2006-2015)
Bibliographic record
Abstract
Using a critical feminist lens, this major research paper examines the state of gender equality in Canada’s foreign policy after a 10 year Conservative government reign. A review of feminist literature demonstrates an erasure of gender equality in foreign policy documents and a corresponding essentializing and instrumentalist discourse surrounding women and girls in key programming and policy. This literature review is enhanced by empirical research with Canadian civil society organizations (CSOs). Interviews with CSO representatives uncovered an overall trend of CSOs being marginalized from policy making between 2006 and 2015. Several core findings support this trend: (1) CSOs perceived a lack of overarching vision in the government approach to gender equality, a vision they were discouraged from constructively and publicly critiquing; (2) there was a freezing of the relationship between CSOs and the government; (3) the role of CSOs in policy making was being changed from advocate and partner to direct service provider; (4) CSOs began to implement new strategies for influence; and (5) CSOs were working in a unique political context whereby CSOs were disconnected from policy making. These findings highlight the overall failure on the part of the Harper Conservatives to promote a transformative agenda for gender equality within Canadian foreign policy.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.060 | 0.027 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".