Enhancing Research With Migrant Women Through Focus Groups
Bibliographic record
Abstract
Recent systematic reviews of measurement strategies have identified a striking lack of data to support the validity of most questionnaires used with multiethnic, migrant populations. In the context of two ongoing research studies examining the reproductive health needs of migrant women in Canada, cultural validation was required for proposed study questionnaires and protocols in a total of 13 languages. Multilingual, multiethnic women with various migrant profiles were recruited from the community to review research materials in a series of focus groups. Recommendations by these women were made in relation to consent and interpretation procedures, development of trust in research, home visits after birth, approaches to sensitive topics, inclusion of discrimination as a research variable, and reimbursement of participants. Preliminary work applying focus-group methods to mixed ethno-cultural groups yielded valuable information on appropriateness of planned research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.171 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".