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Record W7055751156

Does the Cost Barrier to Contraception Differentially Affect Racialized and Indigenous Women? An Intersectional Quantitative Investigation

2022· dissertation· en· W7055751156 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousReproductive healthPopulationAffect (linguistics)Birth controlExploratory researchFertilityBivariate analysisHealth equity
DOInot available

Abstract

fetched live from OpenAlex

Background: In Canada, 15% of sexually active women of reproductive age do not use any form of contraception (Black et al., 2009; Black, Guilbert, Costescu, et al., 2015; Black, Guilbert, Hassan, et al., 2015). The majority of women who do use contraception rely on methods with high failure rates such as condoms only and withdrawal (Black, Guilbert, Costescu, et al., 2015). The most effective forms of birth control, long-acting reversible contraception (LARCs), are underutilized and often the most expensive per unit (Black, Guilbert, Costescu, et al., 2015; Di Meglio & Yorke, 2019). Research has shown that racialized and Indigenous women often have different experiences and barriers to reproductive health care compared to non-racialized and non-Indigenous women (Sutton et al., 2021; Wilson et al., 2013). One factor, cost, has been identified as the most important barrier to using effective contraception (Black, Guilbert, Hassan, et al., 2015; Hulme et al., 2015). \n \nSpecific Aims: Using data from the 2020 Annual Component of the Canadian Community Health Survey (CCHS), this thesis investigates two major questions (1) “Are racialized and Indigenous women less likely to use more expensive and effective forms of birth control than non-racialized and non-Indigenous women?” and (2) “Do differences in contraception use by racialized and Indigenous women, compared to non-racialized non-Indigenous women, appear to be due primarily to financial or cost barriers?”. \n \nMethods: Exploratory data analysis was first conducted in order to present univariate and bivariate distributions of predictor and outcome variables. Bivariate associations included Chi-square tests to examine significance at p >0.05. Three sets of multi-variable binary logistic regression models were then used to assess relationships between outcome and predictor variables. The first set of models examined the binary outcome of Use vs. Non-use, while the second set of models examined LARC contraception use from the sample of women who did use birth control. The last model investigated Use vs. Non-use of contraceptives among specific racial categories. \n \nResults: A large proportion (52.85%) of racialized women reported not using any form of birth control compared to 22.68% of white women and 20.97% of Indigenous women. Higher proportions of racialized women relied on condoms (62.03%) compared to Indigenous (32.91%) and white (35.15%) women. In the first group of binary regression models, racialized women were found to be significantly less likely (OR = 0.766, CI = 0.617, 0.951) to use contraception of any kind regardless of income, education or provincial location. Of the women who reported using contraception, racialized women were found to be significantly less likely (OR = 0.546, CI = 0.365, 0.816) to use LARC forms of birth control. In both sets of models, Indigenous women were not significantly different from white women. In a sub-analysis of only racialized women, Filipino women were found to be significantly less likely (OR = 0.297, CI = 0.129, 0.683) to use birth control of any kind. \n \nConclusion: The findings suggest that the relationship between identity category and contraception use is not fully explained or even impacted by socioeconomic elements such as income and education. These results emphasize the need for further exploration of disaggregated race data pertaining to reproductive health inequities. The results also provide recommendations for Canadian health policy modifications in order to improve contraception access and use among potentially vulnerable populations.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.876
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
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 head0.010
GPT teacher head0.247
Teacher spread0.237 · 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 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
Published2022
Admission routes1
Has abstractyes

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