To breastfeed or not to breastfeed?: an ethnographic exploration of knowledge circulation, medical recommendations on HIV and infant feeding, and related "good" mothering discourses in Saskatoon, Saskatchewan.
Bibliographic record
Abstract
This thesis looks at how knowledge on HIV and infant feeding is circulated, shaped, and then disseminated into a medical recommendation in Saskatoon, Saskatchewan. It explores good/ bad mothering discourses linked to women with HIV who are feeding infants in this city. Guided by Bruno Latour’s actor network theory, I interviewed 31 community and health professionals to ethnographically locate “key actors” involved in knowledge circulation on HIV and breastfeeding. The interviews revealed two patterns of knowledge circulation in which different information on HIV and breastfeeding is being shared. I suggest that contrasting good/bad mothering discourses position women with HIV in a “tension zone” that characterizes them as both ‘good’ and ‘bad’ mothers. I situate my observations in literature on medicalization of reproduction and science studies writings on social movements and “experts”. I argue the tension zone overshadows challenges facing women with HIV navigating poverty and trying to access baby formula.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".