Bibliographic record
Abstract
Adolescence is a time of profound change and development for girls. Canadian girls may face a number of complex issues as they transition through childhood into adolescence, including sharp declines in physical and mental health, high rates of violence at home and at school, and mounting educational and professional pressures. Despite the existence of adversities and developmental challenges during adolescence, girls are remarkably resilient and can be empowered with appropriate supports. By providing positive role models, fostering the development of critical thinking skills, and engaging in leadership-building activities, girls can be supported to reach their full potential (Girls Action Foundation et al., 2013). The organization in the current study, YWCA Edmonton offers such a program. GirlSpace is a comprehensive 20- week program focusing on connecting girls with mentors, building leadership, and fostering critical thinking skills regarding issues commonly faced by adolescent girls. This research used an explanatory sequential mixed-method analysis to evaluate the YWCA Edmonton’s GirlSpace program between September 2017 and March 2018. Twenty-four adolescent girls between the ages of 11 and 17 years participated in the study. The following research questions were the focus of the study: (a) Did completion of the GirlSpace program improve girls’ leadership skills, social connectedness, mental health, and resilience?; (b) Which strengths and assets were developed or improved by the girls in the program, and which of these did they perceive to be most impactful?; (c) Which components of the program did girls find most helpful and unhelpful, and why?, and; (d) How did the themes mentioned by the program participants help to explain any quantitative differences in leadership skills, social connectedness, mental health, and resilience? The overarching goal was to contribute to current and future program delivery through an outcome and program monitoring evaluation. The results of the evaluation were intended to foster resilience and strengths, while mitigating the influence of barriers and limiting the exacerbation of concerns experienced by adolescent girls. Statistical analyses revealed improvements from pre- to post-program on all four measures, with social connectedness displaying the greatest amount of change, followed by mental health, resilience, and leadership, respectively. Thematic analysis corroborated and further explained the quantitative results, highlighted several strengths and assets acquired or improved through program participation, and provided feedback on the helpful and unhelpful components of the GirlSpace program. Overall, this dissertation explores the efficacy of a community-based, after-school program for adolescent girls, with promising effects on participants and constructive recommendations for future GirlSpace programming.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".