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Record W7079643898 · doi:10.26108/wdtv-5r02

How does political culture affect abortion accessibility?: a study of abortion pill access in Nova Scotia and Prince Edward Island

2019· article· en· W7079643898 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2019
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsAbortionNova scotiaPoliticsPillDecriminalizationPolitical cultureAutonomy

Abstract

fetched live from OpenAlex

This thesis asks how political culture impacts accessibility to the abortion pill (Mifegymiso) in Canada by focusing on two case studies, Nova Scotia and Prince Edward Island. Abortions have been decriminalized since the 1980s, yet women in different provinces continue to struggle to acquire access to this legal right and basic autonomy over their own bodies. In Prince Edward Island (PEI), women had a distinct problem with access until very recently, having to request time off and find a referral in order to travel to another province to get access to an abortion. This lack of access can be attributed in large part to the political culture of the province. This thesis takes a most similar cases approach. These two provinces share many commonalities that are useful for this study and have connections in terms of abortion access, as Nova Scotia has frequently provided women from PEI with abortions. For the period of this study, both provinces had the same provincial party in power, and despite their different political culture in the past, their cultural difference gap has since diminished and is no longer evident on this divisive topic and have quite similar policies. By focusing on the years following the decriminalization of abortion, particularly 2015 onward (when the abortion pill was legalized in Canada), this thesis argues that political culture is an important explanatory variable for understanding differences in the abortion policies in these two provinces.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.014
GPT teacher head0.286
Teacher spread0.273 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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