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Record W3117056034 · doi:10.25071/2291-5796.76

A critical feminist discursive analysis of dynamics shaping abortion in Canada: Implications for nursing.

2020· article· en· W3117056034 on OpenAlexafffundvenueabout
Margaret Lebold, Judith A. MacDonnell

Bibliographic record

VenueWitness The Canadian Journal of Critical Nursing Discourse · 2020
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsYork University
FundersCanadian Nurses Foundation
KeywordsAbortionSilenceSociologyGender studiesNormativeContext (archaeology)Political sciencePregnancyLaw

Abstract

fetched live from OpenAlex

The advent of “the abortion pill” (Mifegymiso) in 2015 has shaped the contemporary context of access to abortion in Canada. In this paper, we highlight findings of a literature review that uses a gender and intersectional lens and critical discourse analysis to explore contemporary abortion access and implications for nursing. The discursive dynamics influencing nurses’ understandings of abortion, that is, the contexts in which some discourses are privileged over others yet often operate at the unconscious level to influence everyday knowledge and practices, are important to discern to work towards social justice goals. Findings suggest that normative and contradictory features of discourses such as women’s health, motherhood, and abortion access are relevant. Given the relative silence of abortion in nursing literature and prevailing gender normativity in nursing, there are compelling reasons to apply a critical feminist lens to deepen nurses’ understandings and critical reflection about abortion. There are implications for current education, research, and nursing practice.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.162
Threshold uncertainty score0.972

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0370.035
Scholarly communication0.0140.005
Open science0.0030.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.386
Teacher spread0.341 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes4
Has abstractyes

Explore more

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