A Logistic Regression Analysis of Life Satisfaction amongst African Immigrants in Hamilton, Canada
Bibliographic record
Abstract
Many minority immigrants currently face severe human rights violation through discrimination and racism, influencing how they rate their life satisfaction in their host destinations. This paper examines the factors that affect African immigrants’ life satisfaction in a mid-sized Canadian city. Using a combination of descriptive and multivariate methods applied on a sample survey (n=236) conducted in Hamilton, Ontario, this article investigates socio-demographic and health-related factors that predict life satisfaction amongst African immigrants, specifically, Ghanaians and Somalis. Findings suggest that Ghanaian immigrants reported greater life satisfaction than their Somali counterparts. People with residency in Canada over 10 years are more likely to report higher life satisfaction than those with length of residence from zero to ten years. Older individuals (i.e., age 25-54) are more likely to express higher life satisfaction compared to younger individuals (i.e., 18-24). The findings indicate that socio-demographic conditions matter for immigrants’ life satisfaction
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".