A Whole Community Approach toward Child and Youth Resilience Promotion: A Review of Resilience Literature
Bibliographic record
Abstract
A literature review of child and youth resilience with a focus on: definitions and factors of resilience; relationships between resilience, mental health and social outcomes; evidence for resilience promoting interventions; and implications for reducing health inequities. To conduct the review, the first two following steps were conducted iteratively and informed the third step: 1) Review of published peer-review literature since 2000; and 2) Review of grey literature; and 3) Quasi-realist synthesis of evidence. Evidence from three perspectives were examined: i) whether interventions can improve ‘resilience’ for vulnerable children and youth; ii) whether there is a differential effect among different populations; and, iii) whether there is evidence that resilience interventions ‘close the gap’ on health and social outcome measures. Definitions of resilience vary as do perspectives on it. We argue for a hybrid approach that recognizes the value of combining multiple theoretical perspectives, epistemologies (positivistic and constructivist/interpretive/critical) in studying resilience. Resilience is: a) a process (rather than a single event), b) a continuum (rather than a binary outcome), and c) likely a global concept with specific dimensions. Individual, family and social environmental factors influence resilience. A social determinants perspective on resilience and mental health is emphasized. Programs and interventions to promoting resilience should be complimentary to public health measures addressing the social determinants of health. A whole community approach to resilience is suggested as a step toward closing the public health policy gap. Local initiatives that stimulate a local transformation process are needed. Recognition of each child’s or youth’s intersections of gender, lifestage, family resources within the context of their identity markers fits with a localized approach to resilience promotion and, at the same time, requires recognition of the broader determinants of population health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".