A "Tricky Business" - Knowledge Production in Children's Environmental Health
Bibliographic record
Abstract
Using critical feminist theories and methodologies, my research investigates the power relations and influences at play within the field of children's environmental health. I begin with the research question of how a parent's everyday purchase of a toy or other children's product is "hooked into" extra-local governance (agenda-setting, rule-making and monitoring). Focusing on Bisphenol A and phthalates as an example, in-depth interviews were conducted with six government officials (three federal and three municipal), three non-governmental organization (NGO) representatives, a politician, six higher education faculty members and a parent, as well as two focus groups of 23 parents. Legislation and other relevant documents from governments, NGOs, industry and media were analyzed together with reports of their activities and attitudes to theorize "how things work" in the identification and management of toxic substances in products for sale, with a special interest in how this affects children's environmental health. My research revealed the influence of neo-liberalism, corporate power and over-reliance on strictly evidence-based biomedical reductionism in slowing down assessment and regulation of chemicals while many health professionals and grassroots activists have called for swifter responses based on the precautionary principle, as favoured by European governments. That is, politics and bureaucracy, with the approval of industry, over the past two decades, have clung to reductionist science as the only paradigm for understanding toxicity, thus slowing down regulatory processes. Although the historical and epistemological power relations mapped in my research work together to legitimize scientific certainty rather than the precautionary principle, I argue that the resulting regulatory logjam has been and could be addressed by reference to European examples, knowledge produced by collectives and the establishment of upstream and equity-based public health strategies with public input into the process.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".