The Heart of a Mother, The Waves of Mothering: A Narrative Inquiry into Mothering Experiences of Child Weight Management
Bibliographic record
Abstract
Many stories exist within the professional landscape of child weight management programming and health services. Grand narratives within these spaces story fat bodies as “unhealthy”, “risky” and in need of transformation, and often position the family and mothers in particular given gendered caregiving norms, as responsible for their children’s weight and poor health. Mothering stories and experiences are rarely told by the mothers themselves within this professional landscape. This study is a narrative inquiry that explores the in-depth experiences of two mothers who previously participated with their children in an Ontario paediatric weight management program. Given my work as a social worker within child weight management clinics I also explore my experiences alongside the participants. Clandinin and Connelly’s conceptualization of narrative inquiry and the three dimensional framework of temporality (past, present, future), sociality and place, inquiring inward, outward, backward and forward, were used in order to find meaning in mothering experiences of child weight management. Narrative beginnings share my own experiences of mothering and child weight management. Relational ethics were central as the inquiry unfolded, allowing for simultaneous exploration of experiences, continuous negotiation, awareness and re-evaluation with each mother, from recruitment, field work, to field text, interim text and the writing of the final text. Given the current social distancing restrictions related to the COVID-19 pandemic, conversations took place over zoom and telephone and were audio-recorded and transcribed verbatim. Detailed narrative accounts were written for each mother capturing individual experiences of child weight management as they intersected with many other experiences in their everyday lives. Narrative threads weaved together the mother’s experiences throughout the inquiry and focused on disrupting the grand narrative and resisting fragmentation. The inquiry contributes to the scholarship within fields of social work, social justice, mothering and health care by providing new ways of knowing about and engaging in conversations about mothering, weight, fatness and health.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".