An articulation of the standpoint of peer support workers to inform childbearing program supports in Manitoba First Nation communities: institutional ethnography as de- colonizing methodology
Bibliographic record
Abstract
The dissertation focuses on the work that prenatal peer support workers do in First Nation communities to foster the health of childbearing women. The purpose of the analysis is to unravel system discourses and to retrieve the 'truth' as it is experience articulated by women living in Manitoba First Nation communities today. Several questions are included in the overall analysis. Such as, who guides the women in their work? Who informs, supports, restricts them? How is this women's work connected to the 'bigger picture' of health for pregnant and childbearing First Nation women in Canada? What factors infringed upon the original stories of pregnancy and childbirth in Aboriginal communities resulting in the medicalization and risk discourses that exist today? The main objective of the study is to apply a methodology that allows for an analysis of the everyday work perceptions and experiences of First Nation women employed in their communities to administer childbearing support programs. The local work is analyzed within the context of an institutional picture of health care delivery in Manitoba, Canada. This study is required to raise awareness about the childbearing support work that women do in First Nation communities and to elucidate the bonds that tie this work together with the greater institutional health and social service structures. Such an exploration may highlight the potential of pregnancy and childbirth care to enrich the physical and spiritual lives of First Nation women living in remote, reserve communities.
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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 | 0.043 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.026 | 0.025 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".