Defending Motherhood: Morality, Responsibility, and Double Binds in Feeding Children
Bibliographic record
Abstract
The ideology of intensive mothering sets a high bar and is framed against the specter of the “bad” mother. Poor mothers and mothers of color are especially at risk of being labeled bad mothers. Drawing on 138 in‐depth interviews and ethnographic observations, this study analyzes the discursive and interpersonal strategies poor mothers use to make sense of and defend their feeding and children's body sizes. Food beliefs and practices reflect and reinforce social inequalities and thus represent an exemplary case in which to examine intensive mothering, its ties to growing inequality, and how individuals are called to account for it. Findings demonstrate intersecting inequalities, meanings, and contradictions in mothers' accounts of meeting intensive mothering expectations around feeding, health, and weight. In light of moral framings around feeding and weight, mothers' experiences of surveillance, and the double binds they encounter in feeding children, mothers practice what the authors term defensive mothering.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.025 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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 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".