Care(full) Campaigning? A Feminist Critical Discourse Analysis of Childcare in the 2014 and 2018 Ontario Elections
Bibliographic record
Abstract
<p>Childcare in Ontario continues to face significant challenges both structurally and ideologically. Drawing on feminist ethics of care scholarship (Barnes, 2012; Held, 2006; Tronto, 1993, 2006; Sevenhuijsen, 2003), this study builds on the important work of Langford et al. (2017) in theorizing the care as central to political dialogue and a public good. The study employs a feminist critical discourse analysis (Lazar, 2007; Fairclough, 2003, 2013) to explore conceptualizations of care in childcare in political party platforms and advocate organization responses during the 2014 and 2018 Ontario elections. Analyzing both political party platforms and advocate organizations demonstrated that the economic and human capital rationales dominated. Emerging in 2018 was both a maternal emancipation discourse, and the broad employment of personalization as a discursive strategy. Based on the findings, recommendations for discursive resistance are explored.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".