MétaCan
Menu
Back to cohort
Record W4297198392 · doi:10.47940/cajas.v7i3.595

From Identity to Ecology in the new Bulgarian Cinema: the Unique Case of Àga (2018) and the Poetics of the Icy Wasteland

2022· article· en· W4297198392 on OpenAlexaboutno aff
Andronika Màrtonova

Bibliographic record

VenueCentral Asian Journal of Art Studies · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology, Conservation, and Geographical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterBulgarianPoeticsIdentity (music)AestheticsSociologyHistoryMedia studiesLiteratureArtArt historyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

After the perestroika, the fall of the Berlin Wall and the collapse of the USSR and the socialist bloc, Bulgarian post-totalitarian cinema stands on a new path and contexts, in the milieu of wide East European or Balkan cinema. The film artifact offers a unique opportunity not only to interpret the foreign world, but also to rearrange its own cultural values. The issue of dialogue between identities in the global and contemporary cinema process is definitely extremely interesting, complex and multifaceted. The present study focuses its attention on an internationally recognized co-production – Àga full-length movie (2018, dir. Milko Lazarov, Bulgaria-Germany-France, 96`), shot in the Republic of Sakha (Yakutia). Definitely, this is something new for the national cinema – to realize original themes and stories on the Bulgarian-Asian axis, to introduce the total unused, attractive even personages, often even in a non-Bulgarian cultural environment. The film is among the best of Bulgarians cinema produced since 1989. A very important aspect in Àga is not only the topic of Otherness, but also the strong environmental engagement. The analysis shows that Lazarov`s film is not purely or only ecological, but universal as onscreen suggestions. Àga affects fundamental and universal human categories. Through the language of the closed Inuit community, a kind of microcosm, speaks to the world community – the macro level.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCentral Asian Journal of Art StudiesSame topicEcology, Conservation, and Geographical StudiesFrench-language works237,207