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Record W4318481327 · doi:10.16995/olh.8866

Local and Universal: The Canadian Inuit and the Irish Aran Islanders in the Films of Robert J. Flaherty

2023· article· en· W4318481327 on OpenAlexaboutno aff
Krisztina Kodó

Bibliographic record

VenueOpen Library of Humanities · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIrishEnlightenmentLocalitySociologyPoetryUniversality (dynamical systems)Argument (complex analysis)AestheticsArtPhilosophyEpistemologyLiteratureMedicine

Abstract

fetched live from OpenAlex

The article considers the question of locality and universality regarding two locations and populations: the Inuit of the Canadian North, and the Aran Islanders living off the western coast of Ireland. These locations provide the setting for Robert J. Flaherty’s documentary films Nanook of the North (1922) and Man of Aran (1934). The two films attempt to reveal the essence of human nature through illustrations of human beings living under elemental conditions. Comparing the two films, this article explores tendencies toward locality and universality. It addresses the cinematic medium in relation to Walter Benjamin’s ‘The Work of Art in the Age of Mechanical Reproduction’ (1935) and the effects of the culture industry as described in Max Horkheimer and Theodor Adorno’s critical essay, ‘The Culture Industry: Enlightenment as Mass Deception’ (1944). The article considers whether Flaherty’s films prove wrong Benjamin’s argument that modern technology erases the aura surrounding works of art in pre-technological times. This article argues that the aura of Flaherty’s films may instead be considered an artistic effect that is specific to modern times, expressing the poetic vision of their maker.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0220.012
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.206
Teacher spread0.168 · 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
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

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