Multisystemic Resilience: Learning from Youth in Stressed Environments
Bibliographic record
Abstract
Youth resilience is the product of multiple systems. Still, the biological, psychological, social, and environmental system factors that support youth resilience are incompletely understood. How these factors interact, and the situational and cultural dynamics shaping their interconnectedness, are also under-researched. In response, we report a multi-site case study that is instrumental to understanding multisystemic resilience. It draws on the insights of 52 youth from stressed, oil and gas communities in South Africa (13 young men; 8 young women; average age: 20.28) and Canada (19 young women, 12 young men; average age: 20.77). Deductive and inductive analyses show that youth resilience is informed by a biopsychosocial-ecological system of interacting resources that fit situational and cultural dynamics. This has implications for society’s championship of youth adaptation to stressed environments, including less emphasis on individual resources and more on contextually responsive, systemic changes that will facilitate meso- and macro-system resistance to significant stress.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".