MétaCan
Menu
Back to cohort
Record W4252998212 · doi:10.1386/jepc.6.2.129_1

Welcome to Europe! Linking the EU Parliament LUX Film Prize and the impact of migration films to the emergence of a European public sphere

2015· article· en· W4252998212 on OpenAlexaff
Muhamed Amin

Bibliographic record

VenueJournal of European Popular Culture · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsParliamentPublic sphereAcknowledgementEuropean commissionPolitical sciencePoliticsEuropean unionScope (computer science)Political economySociologyMedia studiesLawPublic administration

Abstract

fetched live from OpenAlex

Abstract Migration films represent an emerging genre of film-making that is increasingly influencing European citizens and policy-makers alike. Through them, we are able to deconstruct negative attitudes about migrants and how they fit into an increasingly cosmopolitan and diverse Europe. In 2008, the EU Parliament created the LUX Film Prize, an award that recognizes European films that embody European traditions, values and integration. In 2009, the prize was awarded to French Director Philippe Lioret’s film Welcome, the story of a Kurdish migrant in France hoping to reach Britain by swimming the English Channel. Despite its fictional scope, it was highly politicized and controversial due to its critical approach of French refugee policies, specifically the L622-1 law prohibiting citizens from offering assistance to undocumented migrants. Following the EU Commission’s acknowledgement of the need to further involve citizens in debates on European issues, this article argues that the LUX Prize is an innovative medium to foster debate and discussion on matters of migration within a wider European public sphere. It has also provided a platform for those outside the political landscape to help shape the discourse on migration, thus reinforcing a more inclusive European civic participation on matters directly affecting them as citizens.

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 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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.048
GPT teacher head0.312
Teacher spread0.264 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of European Popular CultureSame topicEuropean Union Policy and GovernanceFrench-language works237,207