Development of a Cultural Connectedness Scale for First Nations youth.
Bibliographic record
Abstract
Despite a growing recognition of cultural connectedness as an important protective factor for First Nations (FN) peoples' health, there remains a clear need for a conceptual model that organizes, explains, and leads to an understanding of the resiliency mechanisms underlying this concept for FN youth. The current study involved the development of the Cultural Connectedness Scale (CCS) to identify a new scale of cultural connectedness. A sample of 319 FN, Métis, and Inuit youths enrolled in Grades 8-12 from reserve and urban areas in Saskatchewan and Southwestern Ontario, Canada, participated in the current study. A combination of rational expert judgments and empirical data were used to refine the pool of items to a set that is a representative sample of the indicators of the cultural connectedness construct. Exploratory factor analysis (EFA) was used to examine the latent structure of the cultural connectedness items, and a confirmatory factor analysis was used to test the fit of a more parsimonious version of the final EFA model. The resulting 29-item inventory consisted of 3 dimensions: identity, traditions, and spirituality. Criterion validity was demonstrated with cultural connectedness dimensions correlating well with other youth well-being indicators. The conceptualization and operationalization of the cultural connectedness has a number of potential applications both for research and prevention. This study provides an orienting framework that guides measurement of cultural connectedness that researchers need to further explore the role of culture in enhancing resiliency and well-being among FN youth in Canada.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".