Characteristics of refugee healthcare models: A scoping review protocol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Canada is facing the arrival of unparalleled numbers of refugees. Access to quality healthcare is central to ensuring optimal integration into Canadian society (Iqbal et al., 2022). However, their ability to receive care coverage is fragmented by systemic barriers and profound health challenges. Refugee community health centers (CHCs) have been established to provide wrap-around services to refugees upon their arrival (Albrecht, 1998). However, there is sparse scholarly research on their effectiveness in Canada and the existing models that they operate under. Method: A scoping review will be conducted using the PRISMA-ScR checklist for essential reporting (Tricco et al., 2018). In collaboration with a research librarian, articles from four databases will be gathered and uploaded onto Covidence. Grey literature will be incorporated manually. A comprehensive set of inclusion/exclusion criteria will be formulated to screen study titles and abstracts, followed by a thorough review of full texts and data extraction. Significance: Given the increase in refugee resettlement, their unique health needs, and barriers to accessing care, this research will contribute to a limited body of literature by highlighting facilitators to primary healthcare access. This research will be mobilized with refugee community health centres, decision-makers, and the government to inform culturally safe, equitable healthcare practices in Alberta and across Canada. Finally, these findings will inform CHCs of alternate provision of care models. Key words: refugee, community health centre, healthcare, scoping review, access, service models
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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 it