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Record W3013157065

Terugkeerders uit jihadistische strijdgebieden. Een vergelijking tussen Nederland, België, Denemarken, Duitsland, Frankrijk, het VK en de VS

2019· article· nl· W3013157065 on OpenAlexfundno aff
Edwin Bakker, J. Sciarone, Jeanine de Roy van Zuijdewijn

Bibliographic record

VenueLeiden Repository (Leiden University) · 2019
Typearticle
Languagenl
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

In dit vierde rapport in de reeks worden ontwikkelingen besproken ten aanzien van het beleid met betrekking tot personen die terugkeren uit jihadistische strijdgebieden, zogeheten ‘terugkeerders’, voor de periode januari 2017 tot medio december 2018. Bijzondere aandacht wordt geschonken aan de rol van overheden van de zeven landen bij de repatriëring van uitreizigers en de manier waarop zij omgaan met de uitreizigers op het moment van terugkeer. Hierbij wordt specifiek gekeken naar het beleid ten aanzien van vrouwen en kinderen.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.008
Scholarly communication0.0060.003
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0240.003

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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