Maternal responsibilization in times of crisis: transition to motherhood and collective anxiety in Canada
Bibliographic record
Abstract
The first two decades of the twenty-first century have been shaped by a seeming unending series of crises. 9/11, the ’08 Financial Crisis, climate change, and the COVID-19 pandemic have exacerbated perceptions of risk at both collective and individual levels. These events have also brought widespread attention to persistent and intersectional inequalities and have contributed to widespread collective anxiety. In this paper, we aim to understand how crisis and motherhood discourses constitute ‘good mothers’, and how this is navigated and experienced by first-time mothers. To do so, we apply the concept of ‘maternal responsibilization’ to interrogate how maternal subjectivities are activated through contemporary neoliberal governmentality, characterized by crisis, risk, and collective anxiety. Using data from our longitudinal study on first-time mothers in Toronto and Montreal, Canada, we explore how maternal subjects are not merely responsible for the basic well-being of their children, but rather are responsibilized through policy discourse, in which they seek to secure the far-off future health and well-being of both their children and the whole of society. We also illuminate how mothers negotiate these complex maternal subject positions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".