Narratives of smoking relapse: The stories of postpartum women
Bibliographic record
Abstract
Many women who stop smoking during pregnancy relapse soon after the birth of their infants. Using narrative research, experiences of smoking relapse were explored using interviews with 27 postpartum women. The stories of relapse were analyzed to identify important components, paying attention to commonalities, differences, and areas of emphasis. Five general story lines were identified: (1) controlling one's smoking (starting with a "puff" and consciously restricting the amount smoked); (2) being vulnerable to smoking(relapsing because of an inability to resist cigarettes); (3) nostalgia for one's former self(relapsing to recapture feelings of freedom and happier times); (4) smoking for relief(relapsing to manage emotions and stress); and (5) never really having quit (relapsing because they did not quit for themselves). The findings of this study provide support for the claim that the experiences of smoking cessation and relapse among postpartum women may be unique and, consequently, may require specialized intervention.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".