Lies, Damn Lies and Public Protection: Corporate Responsibility and Breast Cancer Activism
Bibliographic record
Abstract
Introduction: The first world conference on breast cancer, held in Kingston, Ontario, in July 1997, provided a unique opportunity for activists, concerned about the possible links between breast cancer and the environment, to share their concerns in an international forum, with oncologists, radiologists, epidemiologists, survivors and alternative therapists. It also clearly exposed the fracture lines between competing discourses of risk and responsibility, between groups charged with a duty to protect and to care - health professionals, epidemiologists, statutory bodies, and those taking on those duties - generally activists, from environmental, feminist and survivor groups. These lines were even more clearly drawn at the second world conference in summer 1999 in Ottawa, particularly by the popular and medical media, which chose to stress the ‘radical’ (i.e. ‘dubious’) claims of many of the papers which considered breast cancer risks from the environment. The fundamental question that concerns me here is an explicitly ethical one: if we must act to prevent harm (and presuming for the moment the not uncontroversial assumption that disease is a harm), that is to say, if we are to act morally, then what counts as necessary and sufficient evidence to act? This, I think, is the ethical dimension to activism neglected or hidden in other formulations; Cuomo, for instance, defines activism as “conscious, purposeful, political activity” (1996:43), which seems to ignore the sense of moral duty and responsibility that characterises confrontational activity from the margins and which I want to consider here.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".