Relationship and Gender Equity Measurement Among Gender-Inclusive Young Women and Non-Binary Youth in British Columbia (RE-IMAGYN BC): Planning a Youth-Led, Community-Based, Qualitative Research Study
Bibliographic record
Abstract
Gender-based power dynamics within intimate relationships such as controlling behaviours are driven by inequitable gender norms that perpetuate intimate partner violence (IPV). Yet, the ways in which we understand and measure gender-based power dynamics focus on the relationships of monogamous, cisgender, white, heterosexual women. This paper outlines our process of planning and implementing a qualitative, youth-led, community-based research (CBR) study exploring how diverse youth with intersecting identities perceive existing measures of gender equity and understand gender equity based on their own relationships. Between August-November 2022, we used purposive sampling to recruit 30 gender-inclusive young women and non-binary youth aged 17–29 with diverse identities, who live in British Columbia (BC), and have recent experience in a non-heterosexual and/or non-monogamous relationship (within prior 12 months). Using CBR methods, we hired and trained three Youth Research Associates (YRAs) and convened a 10-member Youth Advisory Committee (YAC) comprised of youth aged 19–28 years with queer, trans, and/or non-monogamous identities and experiences to consult on all aspects of our study. YRAs conducted cognitive interviews using an interview guide co-developed and piloted in partnership with the YAC and YRAs. Cognitive interviews explored youth perceptions of gender equity and two gender equity measures widely used in health research today. Interview data will be analyzed collaboratively using intersectional descriptive and thematic analysis. Results from our CBR study will be used to make recommendations to advance gender equity measurement to be more inclusive of and applicable to a diversity of youth relationships, experiences, and identities.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.156 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".