Referee report. For: Empowering young immigrant girls in Canada through the ‘Girls’ Voices’ Curriculum: A qualitative study [version 1; peer review: 1 approved with reservations]
Bibliographic record
Abstract
Background: Gender inequality is a global issue. In Canada, 70% of women experience some form of inequality in their lifetime. Immigrant adolescents in Canada make up a substantial proportion of newcomers, and immigrant girls face the threat of subjugation and oppression, which has a significant impact on their health, development, and economic outcomes as well as gender inequality. Research on girls’ empowerment and resilience-building programs and interventions is virtually nonexistent. In this project, we implemented the ‘Girls’ Voices’ Curriculum. The aim of this project was to engage and empower South Asian (SA) immigrant adolescent girls and to promote gender equality in Canada. Methods: This study utilized a qualitative descriptive design. Pre- and post-curriculum implementation focus group discussions were conducted. Results: A total of 16 adolescent girls ranging from 11 to 18 years of age participated in this study. The participants described challenges many young girls face in relation to gender inequality such as gender discrimination, gendered stereotyping, barriers to education, etc. The ‘Girls’ Voices’ Curriculum allowed participants to highlight and reflect on the various problems faced by SA immigrant adolescents in their communities. The participants learned to examine these challenges through a variety of engaging activities to identify their root cause, effects and propose solutions to bring long-lasting change. The curriculum equipped them with useful tools such as decision-makers maps and advocacy skills to educate decision-makers by creating and delivering powerful messages influenced by personal stories and evidence-based literature. Conclusion: The study provided significant insight into understanding the diverse challenges encountered by SA immigrant adolescent girls in Canada and linking them to the effectiveness of the ‘Girls’ Voices’ Curriculum. The girl-focused development programs that emphasize developing self-confidence, communication skills, problem-solving skills, and decision making are effective in empowering the socially deprived adolescent girls locally and in the global context.
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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 | 0.010 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.223 | 0.049 |
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".