A qualitative study of how young women in a rural Canadian community plan their futures
Bibliographic record
Abstract
Education and employment are well-acknowledged social determinants of health. However, little is known about how young women in rural, resource-dependent communities make decisions about postsecondary education, employment, and other aspects of their futures. To address this gap, we conducted a qualitative study with young women (ages 16-19) in a rural, oil and gas town in Alberta, Canada. Our overarching research question was, how do young women living in this town imagine and plan for their futures? We conducted 16 one-on-one interviews in 2022 and analysed them using reflexive thematic analysis. Through this process, we developed two main themes. The first main theme of 'challenging gendered social and economic relations' has three subthemes: (i) feeling frustrated with the inattention to girls' lives, (ii) admiring independent women who defy gender norms, and (iii) desiring financial self-sufficiency in response to economic instability. The second main theme of 'negotiating ambivalence about belonging' has three subthemes: (i) facing the double edge of belonging, (ii) transitioning professional, queer, and political identities, and (iii) holding space for ambivalence. Overall, this study generated insight into young women's experiences of growing up and living in a rural, oil and gas town, which helped us map out how these experiences shaped their future plans. Better understanding the perspectives of young women in resource-dependent communities is important for informing the design of interventions targeting their health and well-being, such as those encouraging the uptake of postsecondary education.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".