The causal in fluence of social capital on immigrant health conditions in Canada
Bibliographic record
Abstract
Using a representative longitudinal survey of the immigrant population in Canada (the "Longitudinal Survey of Immigrants in Canada"), this article assesses the causal influence of social capital (as measured by social participation) on immigrant health status and health care use. \nFurthermore, it sheds light on the relationship existing between social capital, human capital and immigrant health conditions. We begin with Probit models but then address the identification issue of social capital using several bivariate dynamic Probit models. Estimation results are consistent with exiting literature since we nd a positive in uence of social participation \non immigrant health status and health care use. Moreover, our analyses reveal that some social activities are more protective than others such as participation to sporting groups, church \ngroups, cultural clubs or political associations. More importantly, the effect of social capital on \nimmigrant health conditions seems to differ according to their human capital level, measured through educational attainment. In this respect, social capital appears to act as a substitute \nfor human capital to enhance immigrant health status while we found a complementary effect between social and human capital to increase immigrant health care utilisation.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".