Social network mechanisms of ethnic inequalities in smoking among adolescents
Bibliographic record
Abstract
Despite decreasing overall smoking rates, ethnic inequalities in smoking persist. Although smoking is largely a social behavior, the underlying social network mechanisms for this are still unclear. We disentangled and tested potential social network mechanisms responsible for persistent ethnic inequalities in smoking. We applied Stochastic Actor-Oriented Models for 1644 friendships of 299 Roma and Non-Roma Hungarian adolescents in nine classes and 1605 antipathies of 294 adolescents in eight school classes over two panel waves. Adolescents were more likely to nominate same-ethnic peers as friends [odds ratio (OR) of Non-Roma nominating a Non-Roma = 1.15; 95% confidence interval (CI) = 1.03-1.28] and less likely to nominate them as antipathies (OR of Roma nominating a Roma = 0.77; 95% CI = 0.68-0.87). Smokers were more likely than non-smokers to receive friendship nominations (OR = 1.18; 95% CI = 1.01-1.38) but did not statistically significantly differ in antipathy nominations (OR = 1.16; 95% CI = 0.97-1.39). Non-Roma smokers tended to nominate as friends other Non-Roma smokers (OR = 1.37; 95% CI = 1.12-1.68) and avoided nominating Roma non-smokers (OR = 0.55; 95% CI = 0.35-0.87). Neither friends (OR = 1.28; 95% CI = 0.88-1.86) nor antipathies (OR = 1.15; 95% CI = 0.69-1.91) influenced peers' smoking behaviors significantly. We identified three processes that could potentially contribute to ethnic smoking inequalities: (i) adolescents tend to nominate same-ethnic peers as friends, (ii) smokers are attractive for friendship selection, and (iii) Roma received higher encouragement to smoke than Non-Roma since Non-Roma received more while Roma received less friendship nomination from Non-Roma peers if they do not smoke. We found no impact of antipathy on smoking.
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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 | 0.023 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".