Numeracy and Health Numeracy Among Chinese and Kenyan Immigrants to Canada
Bibliographic record
Abstract
Mathematics self-efficacy plays an important role in the performance of quantitative tasks. The objective of this study was to examine the role of mathematics self-efficacy in numeracy and health numeracy among immigrants (60 Mandarin-speaking and 60 Kikuyu-speaking immigrants to Canada) for whom English was a second language (ESL). Two French Kit numeracy tasks (the addition, and the addition and subtraction correction tasks) constituted objective measures of numeracy, and the numeracy component of a health literacy instrument (The Short Test of Functional Health Literacy for Adults [S-TOFHLA]) constituted the health numeracy measure. We measured math self-efficacy using the Mathematics Self-Efficacy Scale (MSES) and the Subjective Numeracy Scale (SNS). All measures were presented in English. Kikuyu speakers had lower math self-efficacy ( p < .05) compared with Mandarin speakers ( p < .05). Mandarin speakers outperformed Kikuyu speakers in numeracy ( p < .001) and health numeracy ( p < .023) skills. In multiple regression analyses, 32% to 57 % of the variance in objective numeracy was explained by language, residency in Canada, and self-efficacy, adjusting for the other predictor variables; self-efficacy and format of numeric health information (numbers only vs. numbers with detailed text) consistently predicted health numeracy. Mathematics self-efficacy may be an important factor in numeracy, but not as important in health numeracy for Kikuyu- and Mandarin-speaking immigrants for whom English is a second language. Factors contributing to low numeracy may differ from those explaining low health numeracy in ESL immigrants.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".