La configuración de la maternidad a través de la inversión social en los niños. Ejemplos de Canadá y México
Bibliographic record
Abstract
As post-neoliberal scholars have pointed out, social investment targeting risk groups has be- come the focus of social spending by states in many countries around the world, and children, given their inherent potential, have increasingly become the focus of state investments aimed at enhancing their future integration into the market economy. This chapter details the results of two case studies which examine the regulation of motherhood in very different contexts where neo-liberal techniques target investment in children. In Canada recent campaigns have urged mothers to invest heavily in their children during their early years in order to enhance brain development and future market success. In Mexico, the state-sponsored anti-poverty program aims to increase children’s human capital development through the educational system as a way to ensure the future insertion of rural Mexicans into the market economy. The results of in-depth interviews with mothers in southern Ontario and rural Mexico are compared, and while the there are many class-based and cultural differences in the experiences of these mothers, there are also some surprising similarities in terms of the effects of a social investment framework on the regulation of motherhood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".