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Record W4285578941 · doi:10.4000/diasporas.5573

Négocier l’accueil de réfugiés sans réfugiés. Mobilisation associative canadienne et catégorisation du réfugié durant la Seconde Guerre mondiale

2020· article· fr· W4285578941 on OpenAlexaffabout
Annelise Rodrigo

Bibliographic record

VenueDiasporas · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsCanadian Society for the History of Medicine
Fundersnot available
KeywordsRefugeeHumanitiesPolitical scienceEthnologyWorld War IIArtSociologyLaw

Abstract

fetched live from OpenAlex

Durant la Seconde Guerre mondiale, le Canada n’accueille qu’un petit nombre de réfugiés. Cet article vise à étudier les négociations menées par un réseau associatif ayant à sa tête deux associations – le Congrès juif canadien et le Canadian National Committee on Refugees [CNCR] – pour faire admettre des réfugiés au pays. Les dirigeants juifs et les membres du CNCR développent à la fois des négociations externes avec le gouvernement fédéral et des discussions internes au sein même du réseau associatif afin de présenter les réfugiés comme des migrants utiles, des migrants idéaux.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Qualitativelow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2020
Admission routes2
Has abstractyes

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