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Record W2790935638 · doi:10.1080/02646838.2018.1442919

‘Removed from humanity’: a qualitative analysis of attitudes toward abortion providers in anti-abortion individuals in Canada

2018· article· en· W2790935638 on OpenAlexaffabout
Kari N. Duerksen, Karen Lawson

Bibliographic record

VenueJournal of Reproductive and Infant Psychology · 2018
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of SaskatchewanUniversity of Victoria
Fundersnot available
KeywordsAbortionThematic analysisQualitative researchMedicineSocial psychologyPsychologyFamily medicinePregnancySociology

Abstract

fetched live from OpenAlex

OBJECTIVE: The present study explores the content of abortion provider stigma. BACKGROUND: Abortion stigma extends beyond women who have abortions to abortion providers. Previous analyses of anti-abortion bills and rhetoric have revealed stereotypes of abortion providers as dangerous and less trustworthy than other health professionals. METHODS: We present a thematic analysis of one-on-one interviews about attitudes toward abortion providers with Canadian individuals (N = 21) holding an anti-abortion stance. RESULTS: We found participants held two kinds of beliefs about abortion providers: (1) providers are agentic and intentional actors and (2) providers are non-agentic victims of a larger system. While the former subtype of provider was viewed with hostility and disgust, the latter was viewed with pity, with participants suggesting that restriction of abortion would be beneficial for provider well-being. CONCLUSION: We document a new component of abortion provider stigma: the belief that abortion providers are harmed by abortion and that they are to be pitied for this. This 'abortion harms providers' attitude parallels recent anti-abortion arguments that abortion harms women. These stigmatising attitudes both construct the provider as untrustworthy and unable to properly care for women.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.047
GPT teacher head0.416
Teacher spread0.369 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2018
Admission routes2
Has abstractyes

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