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Record W4312061285 · doi:10.18357/bigr41202221093

Daha: “Chasing More Hope, Questing More Humanity”

2022· article· en· W4312061285 on OpenAlexvenueno aff
Medine Derya Canpolat

Bibliographic record

VenueBorders in Globalization Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterHumanityPlot (graphics)NarrativeTurkishPerspective (graphical)ImmigrationSociologyMedia studiesHistoryPolitical scienceLawVisual artsArtLiteratureArt historyPhilosophy

Abstract

fetched live from OpenAlex

The 2018 Turkish film Daha, inspired by Hakan Günday's novel and directed by Onur Saylak, deals with the experiences of immigrants during border crossings and the migrant smuggling networks through the father and son relationship. It is the second film directed by Saylak, one of the most well-known actors in Turkey. Saylak explains that he directed this film with the motivation that cinema should teach people and the aim that makes the audience consider the topic of the film. Daha takes place in Kandalı, a fictional town on the Aegean coast of Turkey where migrant smuggling is intense. It indicates the journey of the migrant smuggled by sea, and presents the migrant smuggling networks and the actors who have different roles in this network: the smuggler, the leader of the safe house, and the boat owners. Ahad, the smuggler, and his 14 years-old son Gaza, the leader of the safe house, are the starring of the film. The plot of the film is presented from Gaza's perspective and narration. The text "the first tool used by a human is another person" reflected on the screen at the beginning of the film draws attention to migrant smuggling.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.384
Teacher spread0.356 · 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
Published2022
Admission routes1
Has abstractyes

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