MétaCan
Menu
Back to cohort
Record W2762442610 · doi:10.1139/facets-2017-0059

“I kind of feel like sometimes I am shoving it under the carpet”: Documenting women’s experiences with post-abortion support in Ontario

2017· article· en· W2762442610 on OpenAlexafffundvenueabout
Kathryn J. LaRoche, Angel M. Foster

Bibliographic record

VenueFACETS · 2017
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsInstitute of Population and Public HealthUniversity of Ottawa
FundersOntario Ministry of Health and Long-Term CareUniversity of Ottawa
KeywordsAbortionDirectiveService providerMedicineService (business)Family medicinePsychologyPregnancyBusiness

Abstract

fetched live from OpenAlex

Background: Abortion has been available without criminal restriction in Canada since 1988, and approximately 33 000 terminations take place in Ontario each year. Objectives: This study aimed to explore women’s expressed desire for post-abortion support services, document the priorities expressed by women in seeking post-abortion support, and identify actionable strategies to improve post-abortion support services in Ontario. Methods: Between 2012 and 2014 we conducted in-depth, open-ended interviews with 60 Anglophone women from across Ontario who had recently had an abortion. We aimed to rigorously explore the compounding issues of age and geography on women’s abortion experiences. We analyzed our data for content and themes and reported on the findings related to post-abortion support. Results: One third of our participants expressed a desire for post-abortion support, yet few were able to access a timely, affordable, non-directive service. Women were uncertain about how to find services; most contacted a provider recommended by the clinic or searched online. Women were enthusiastic about a talkline format citing anonymity and convenience as the main advantages. Conclusion: Our results suggest that exploring ways to expand post-abortion support services in Ontario is warranted. A talkline format could provide an anonymous, convenient, non-judgmental, and non-directive way to address this unmet need.

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)0.001
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 score0.083
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.302
Teacher spread0.280 · 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

Citations11
Published2017
Admission routes4
Has abstractyes

Explore more

Same venueFACETSSame topicReproductive Health and ContraceptionFrench-language works237,207