MétaCan
Menu
Back to cohort
Record W4317424965 · doi:10.1080/08865655.2023.2168292

Resistance to Denmark’s Ad Hoc Campaign Against Asylum Seekers

2023· article· en· W4317424965 on OpenAlexvenueno aff
Melissa Wall

Bibliographic record

VenueJournal of Borderlands Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersCollege of Communication Arts and Sciences, Michigan State University
KeywordsRefugeePolitical sciencePost-hoc analysisResistance (ecology)CriminologyPsychologyMedicineLawBiology

Abstract

fetched live from OpenAlex

This paper examines actions taken in response to the Danish government’s use of policies and public communications to try to asylum seekers crossing its border. Drawing on interviews with grassroots civil society organizations and refugees as well as assessment of refugee-oriented public projects, this analysis finds that civil society and refugees engaged in a range of actions to resist national policies. Such actions included the production of alternative narratives about borders, prioritizing humanitarian practices, and highlighting asylum seekers’ lived experiences as important forms of border and migration knowledge and expertise.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.340
Teacher spread0.311 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Borderlands StudiesSame topicMigration, Refugees, and IntegrationFrench-language works237,207