MétaCan
Menu
Back to cohort
Record W7019473094

“Friends, Partners, Allies” at a Crossroad : A comparative analysis of Canada, the United States, and Islamic State-affiliated citizen repatriation from Northeast Syria

2023· other· en· W7019473094 on OpenAlexaboutno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRepatriationIslamMilitantState (computer science)RefugeeForeign policySecuritizationComparative caseEthnography
DOInot available

Abstract

fetched live from OpenAlex

Since the 2019 territorial defeat of the Islamic State (IS) in northeastern Syria, thousands of foreign nationals affiliated with the Islamic militant group have been detained in refugee camps and prisons in the region - the humanitarian conditions of which have come under increased scrutiny. As a result, the repatriation of these individuals has become a contentious migration-related policy issue and has led to diverse state responses. In the North American context, there is a striking contrast between Canada’s ‘passive’ approach and the United States’ ‘active’ role in these repatriation efforts. Through a comparative critical discourse analysis (CDA) using Fairclough’s methodological three-step framework and Balzacq’s sociological securitization theory, the public rationale of Canadian-American policy diversion is explored. As a result, this study contributes new knowledge to the field, providing unique insights on how and why two closely-allied countries justify their engagement with IS- affiliated citizens in fundamentally different ways.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.523

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.011
Science and technology studies0.0320.011
Scholarly communication0.0090.004
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.285
Teacher spread0.261 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueKTH Publication Database DiVA (KTH Royal Institute of Technology)French-language works237,207