Exploring economic and health interventions to support adolescents’ resilience and coping in mining communities: A scoping review
Bibliographic record
Abstract
Economic and social disruptions, such as the global COVID-19 pandemic, heighten the vulnerability of adolescents. These disruptions exacerbate health and economic inequities which are further compounded in informal labour settings such as the mining sector. Therefore, strengthening adolescent resilience and coping are crucial for well-being and equitable health outcomes. However, there is a limited comprehensive literature that synthesizes adolescent resilience interventions, especially in mining communities. This study presents a scoping review, following Arksey & O'Malley's (2005) framework, to map existing literature on interventions for adolescent resilience in mining communities. Relevant studies were identified from academic journals and grey literature published between 2012 and 2022. Of the 1286 studies screened, 13 were retained for final analysis. Literature showed that common economic resilience interventions included policy-level advocacy and activism, and predominant health interventions focused on sexual and reproductive health including, HIV counselling, screening, and testing, targeting both individual and community-level change in mining communities. The findings emphasize the necessity for interventions to adopt multi-level, multi-sectoral, and multi-stakeholder approaches, while mainstreaming gender. Future research should prioritize intersectional, gender-transformative and community-based interventions to strengthen adolescent resilience in mining communities and advance health equity and rights amongst this last-mile population.
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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 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".