Pathologizing or Validating: Intake Workers' Discursive Constructions of Mothers
Bibliographic record
Abstract
We employ a feminist discursive lens to re-examine an earlier thematic-based analysis of intake workers' reports of interviews with mothers at a children's hospital. In the original study the first author focused on coping styles of parents of children with exceptionalities, whereas in the current study we demonstrate how intake workers' discursive constructions of mothers as pathological functions to dismiss mothers' views and concerns, and constructions of sets of parents as open to expert advice functions to validate them as "effective allies." In this article, we seek to provide an example of how our analytical lens serves to produce various findings that might serve the voices of the more powerful, or of the marginalized. As an outcome of the re-analysis of the data, we recommend an approach to parent- professional interaction that involves enacting language that fosters mutual respect between professionals and parents, and in particular between intake workers and mothers.
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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 | 0.027 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.038 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.011 |
| 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".