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Record W2955881763 · doi:10.1097/mph.0000000000001524

Syrian Refugees and Their Impact on Health Service Delivery in the Pediatric Hematology/Oncology Clinics Across Canada

2019· article· en· W2955881763 on OpenAlexaffabout
Rachid Barry, Christine Chretien, Melanie Kirby, Gloria Gallant, Sarah Leppington, Nancy Robitaille, Catherine Corriveau‐Bourque, Jayson Stoffman, John K. Wu, Michael Leaker, Robert J. Klaassen

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2019
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsAlberta Children's HospitalBC Children's HospitalChildren's Hospital Research Institute of ManitobaCentre Hospitalier Universitaire Sainte-JustineLondon Health Sciences CentreIzaak Walton Killam Health CentreStollery Children's HospitalHospital for Sick ChildrenChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineWorkloadRefugeeSyrian refugeesHematologyFamily medicineImmigrationHealth carePopulationInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

This study examined the impact of Syrian refugees on 1 area of the Canadian health care sector. We predicted that pediatric hematology clinics across Canada would see a spike in their Syrian refugee patient population in proportion to their recent migration and, as a result, an increase in perceived workload. Data on the number of refugee patients, types of diseases, and perceived workload were gathered from hematology clinics across Canada using a clinical survey (Supplemental Digital Content 1, http://links.lww.com/JPHO/A315). The results showed that Ontario had the most Syrian refugee patients, followed by the Quebec, Western Canadian, and Atlantic regions. The results also showed that perceived workload ranged from "no increase" (4 programs) to "minimal increase" <25% (1 program), "moderate increase" 25% to 75% (4 programs), and "significant increase" >75% (3 programs, 2 of which had no transfusion-dependent thalassemia patients before the immigration).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.024
GPT teacher head0.388
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2019
Admission routes2
Has abstractyes

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Same venueJournal of Pediatric Hematology/OncologySame topicMigration, Health and TraumaFrench-language works237,207