The Neoliberal Politics of the Child: Violence Against Women and Mother/Child Welfare, 1990-2012
Bibliographic record
Abstract
This thesis examines violence against women, mothers and child welfare in Canada and Ontario from 1990 to 2012. It explores policy evolution during this perfect storm of intensified neoliberalism and the turn to the child in policy agendas, tracing the complexities of politics and policy at federal, provincial and institutional levels. Feminist political economy, feminist standpoint epistemology and intersectional theorizing provide a complimentary race, gender and class analysis of the structural and systemic inequalities encountered by women and their children seeking violence-free lives. Mixed methods of policy mapping, forty semi-structured qualitative interviews with state and non-state actors and two focus groups with abused mothers are used to connect policy to the lived experiences of abused mothers, single fathers, social workers, and managers. \nThis study shows the decentralization of federal policy power to the provinces, the withering federal investment in income inequality, and the narrow focus on early childhood education bode ill for women fleeing violence. The restructuring of Ontario policies and practices around the at-risk child under the Harris Conservatives that continued under the McGuinty Liberals, depoliticized violence against women initiatives and retrenched colonial, gendered and racialized violence against women and children. Furthermore, the policy shift to the child eclipsed womens equality issues, such as ending violence against women, redressing womens poverty, and mitigating the structural inequality of womens unwaged caring labour with children. With the rise of a child welfare state focused on child risk, objective managerialism, and failure to protect policies, social workers and managers supporting families criticize these anti-feminist policies and practices that promote the hyper-responsibility of mothers to protect their children to the exclusion of fathers. As women with children flee violence transition to single mother families, their futures are seriously constrained by state-mandated child protection work and increased state monitoring of their lives. Alternative visions for transformative change include hybrid models of state and non-state engagement that place survivor alliances at the centre of policy agendas and policy development. This gives us hope for a different future for women with children facing violence.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".