How People on Social Assistance Perceive, Experience, and Improve Oral Health
Bibliographic record
Abstract
Oral diseases are highly prevalent among people on social assistance. Despite benefiting from public dental coverage in North America, these people rarely consult the dentist. One possible reason is rooted in their perception of oral health and the means to improve it. To respond to this question, largely unexplored, we conducted qualitative research through 8 focus groups and 15 individual interviews in Montreal (Canada). Thematic analysis revealed that people on social assistance: (a) define oral health in a social manner, placing tremendous value on dental appearance; (b) complain about the decline of their dental appearance and its devastating impact on self-esteem, social interaction, and employability; and (c) feel powerless to improve their oral health and therefore contemplate extractions and complete dentures. Our research demonstrates that perception of oral health strongly influences treatment preference and explains low and selective use of dental services in this disadvantaged population.
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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 | 0.001 | 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 | 0.001 |
| 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".