MétaCan
Menu
Back to cohort
Record W3217504687 · doi:10.3167/latiss.2021.140303

Understanding networks of actors involved in refugee access to higher education in Canada, England and France

2021· article· en· W3217504687 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLearning and Teaching · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsWestern University
FundersUniversiteit van Amsterdam
KeywordsRefugeeGovernment (linguistics)Civil societyHigher educationContext (archaeology)Political scienceEconomic growthAccess to Higher EducationPublic administrationSociologyPublic relationsPoliticsLawGeography

Abstract

fetched live from OpenAlex

In times of intense migrations, securing a brighter future through education has become a growing concern in many societies. In particular, access to higher education for refugees has been the object of multiple initiatives among governments, civil society and non-government organisations. However, only 3 per cent of refugees access higher education, and there is a need to better understand, support and develop successful access for refugees among policymakers, educators and researchers. This research takes an original comparative digital approach to identifying those networks in three countries: Canada, England and France. Our findings suggest that the nature of issues for refugee access to higher education is constructed differently in each national context, as the social relations between government, civil society, non-government agencies and higher education institutions are uniquely configured.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.254
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.336
Teacher spread0.298 · 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