I am because I have to be: Exploring one mother‐worker's identity of the surrendered self through stories of mothering neurodiverse children
Bibliographic record
Abstract
Abstract Our qualitative study delves into the life history of a mother‐worker caring for two neurodiverse children, surfacing how the intensive mental load of balancing domestic and professional responsibilities permeates and shapes her identity. Employing narrative analysis and photovoice methods, we investigate how she navigates the logistical and emotional complexities in both roles across three distinct storytelling events: storying (mis)diagnoses, storying care needs and work negotiations, and storying coping. Our primary contribution lies in introducing the concept of the surrendered self, signaling the amplified and prolonged embodiment of one's provisional identity (mother) based on socio‐cultural expectations of who she thinks she ought to be, leading to the eclipse of other possible identities (woman, wife, worker).
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".