Risk, responsibility, resistance
Bibliographic record
Abstract
The introduction of human papillomavirus (HPV) vaccination has resulted in a proliferation of discourse about HPV-related health risks, with a particular emphasis on the link between HPV and cervical cancer. Using a discursive narrative approach, we critically examine how young women navigate and construct their identities in relation to discourses on HPV vaccination, and the master narratives of risk, medicalization and individual responsibility for health that inform these discourses. Drawing on positioning theory, the narratives of three women who accepted, declined and were undecided about vaccination are presented to illustrate how they actively and uniquely negotiate their identities in relation to the positions idealized by HPV vaccination discourse, and in the context of their intimate relations and everyday lives. These findings fundamentally challenge dominant techno-scientific perspectives on health risk that underpin the majority of research on HPV vaccine decision-making, and health promotion research more generally. We suggest that discursive narrative approaches can advance critical understanding of how health risk discourse, and emerging technologies aimed at reducing health risks, are implicated in promoting neoliberal constructions of healthy citizenship that frame health risk management as an individual responsibility and moral obligation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.061 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".