Conceptual understanding of social capital in a First Nations community: a social determinant of oral health in children
Bibliographic record
Abstract
Objectives. The purpose of the study was: (a) to better understand the concept of social capital and its potential role in oral health of children in a First Nations community and (b) to identify the strengths and resources in terms of social capital and a health promotion model that the community has at its disposal to address its oral health issues. Methods. In this qualitative case study, participants were purposively selected in a First Nations community: Seven individual interviews and two focus groups involving 18 parents/care givers were selected. Putnam's concept of social capital guided all the interviews. The interviews were recorded and transcribed verbatim. Thematic analysis was employed using the NVivo software. Results. The community was close-knit and seemed to have strong moral fibre, which encouraged members to help each other. A strong bonding social capital was also found among the members, especially inside the clans (families). A need for improvement in bridging social capital that would help the community to reach external resources was observed. While members of the community were actively involved in religious rituals and cultural ceremonies, more efforts seemed to be required to recruit volunteers for other events or programs. Active engagement of community members in any program requires that members be given a voice as well as some ownership of the process. Mobilizing or building community's social capital can play a role when planning future interventions. Conclusions. A better understanding of social capital may enhance the community's investment and efforts by reinforcing healthy oral behaviours and improving access to external resources. With more dynamic collaboration, it may be possible to create more sustainable community-based oral health promotion programs.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".