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Record W7154841387 · doi:10.59236/emro.v27i10a128

Asog

2025· article· W7154841387 on OpenAlexaboutno aff
Johnnie N. Gray

Bibliographic record

VenueEducational Media Reviews Online · 2025
Typearticle
Language
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterDepictionShort FilmFilm directorFeature filmTheme (computing)

Abstract

fetched live from OpenAlex

Distributed by Film MovementProduced by Rey Aclao, Seán Devlin, and Arnel PabloDirected by Seán Devlin2023, Streaming, 101 mins Asog is a film that almost defies categorization. Residents of Sicogon Island reel from the aftereffects of Super Typhoon Hiyan. No trained actors were used for the film; scenes were mostly improvised, which leads to a realistic depiction of people documenting their lives after the typhoon. Part documentary, part drama, part comedy; Asog follows Rey “Jaya” Aclao, a transgender comedian who ventures out after losing their teaching job to go on a road trip to possible win money at a drag show. Along the way, Jaya meets people with specific stories of how their life was changed by the massive storm. Not only is death ever present, but environmental impact, displacement of ancestral lands and climate change are all touched on and make for a very compelling story. Enjoyable and entertaining. An interesting film from the Philippines. Suitable for those studying that part of the world, Philippine culture, or climate change. Adults would be able to understand the intricacies of the film better than those in grade school. Suitable for higher education and general viewing. Awards:Audience Award, Vancouver International Film Festival; Best Feature Film Critics Prize, Ibiza Cinema Fest; Best Film, Hawaii International Film Festival; Outstanding Screenwriting, L.A. Outfest; Frameline Completion Fund, Frameline International LGBTQ Film Festival

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.882
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8820.770

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 head0.042
GPT teacher head0.327
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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Same venueEducational Media Reviews OnlineSame topicSouth Asian Cinema and CultureFrench-language works237,207