Virtues, Resilience, and Well-Being of Indigenous Youth in Peru
Bibliographic record
Abstract
Objectives: The objective of this study was to observe the relation of Values In Action (VIA) virtues, well-being, and resilience within a unique, non-Western population of Indigenous youth in the Peruvian Amazon.Methods: Data were collected from students (n = 172, age range: 11-16 years) attending a rural village school via self-report surveys to assess relationships using the VIA Youth-96 (VIA-Y-96) Assessment, Personal Wellbeing Index (PWI-A), and the Child and Youth Resilience Measure (CYRM-28).Results: The factor analysis of the CYRM-28 yielded a 3-factor breakdown (Social Engagement, Cultural Citizenship, and Guidance) instead of eight. Different VIA virtues predicted each of the three factors of the revised 3-factor CYRM-21-Peru model (CYRM-21-P); Transcendence, Humanity, and Wisdom were predictors of well-being; and higher reported resilience leads to higher well-being. Most participants scored very high on the PWI-A.Implications: Research presented in this paper involved a unique population of Indigenous youth residing in the Peruvian Amazon, and found that (a) VIA virtues were differentially associated with well-being, (b) Humanity was a significant predictor across Cultural Citizenship and Social Engagement in the revised CYRM-21-P, and (c) higher resilience was correlated with higher well-being. Implications of this research can be used to inspire future research of Indigenous populations in a Latin American context to develop youth development programs that teach students from a strength-based perspective to improve vocational, academic, psychological, and social well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".