MétaCan
Menu
Back to cohort
Record W4394822021 · doi:10.1177/14647001241238622

Medicalisation, depoliticisation and reproductive stratification: lessons from Canada's Muskoka Initiative

2024· article· en· W4394822021 on OpenAlex
Jacqueline Potvin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFeminist Theory · 2024
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of GuelphWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPolitical scienceSociologyGender studiesStratification (seeds)

Abstract

fetched live from OpenAlex

Based on critical discourse analysis of Canada's Muskoka Initiative (2010-15), this article outlines how medicalisation contributes to the depoliticisation and technocratisation of global maternal health, while reinforcing patterns of reproductive stratification. By constructing maternal health as a problem of managing medicalised risk, the Muskoka Initiative was able to position family planning as a risk-minimising practice that can improve health by averting pregnancy among populations deemed high risk. Interpreting this construction through the lenses of reproductive justice and biopolitics, I argue that this construction contributes to reproductive stratification and exemplifies how medicalised discourses have replaced overt discourses of population control within development policy, while continuing to discourage reproduction among racialised women in the Global South.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.327
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it