How do women manage the spoiled identity of a ‘pregnant smoker’? An analysis of discursive silencing in women's accounts
Bibliographic record
Abstract
Drawing on public and private accounts of smoking during pregnancy (interviews, survey responses, and a public media article), we examine how women discursively manage the ‘spoiled’ identity associated with inhabiting the body of a ‘pregnant smoker’. We focus on two salient identities ‘the silenced smoker’ and ‘the bad mother’ and explore the discursive and material consequences of these identities. We found that references to smoker and maternal identities were largely absent in women's accounts, and discuss how these absences enabled women to evade stigma and the rhetorical harm of these identities. Further, we discuss the material consequences of stigma including women's need to conceal their ‘pregnant smoker’ body in the face of heightened surveillance. We propose ‘discursive silencing’ to explain how dominant motherhood and anti-smoking discourses serve to render women's experiences as ‘untellable’ and therefore reduce women's capacity to seek help or support to quit smoking.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".