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Record W4399044936 · doi:10.7202/1111033ar

Happiness Is Not Always Fun: An Unsuspicious Reading of <i>Ali: Fear Eats the Soul</i>

2023· article· en· W4399044936 on OpenAlexvenueno aff
Naomi Hodgson

Bibliographic record

VenuePhilosophical Inquiry in Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
FundersKU Leuven
KeywordsSoulHappinessReading (process)PsychologySocial psychologyPhilosophyTheologyLinguistics

Abstract

fetched live from OpenAlex

The film-philosophy of Stanley Cavell has had a clear and ongoing influence on the recent focus on film in educational philosophy. Here, Cavell’s film-philosophy is brought into conversation with the work of the anthropologist Veena Das and the literary theorist Toril Moi to further articulate the educational force of film. The practice of responding to film in terms of its specificity as film and its educational potential is discussed in relation to R. W. Fassbinder’s film Ali: Fear Eats the Soul. Cavell, Das, and Moi are drawn upon to articulate, in a post-critical vein, the invitation to self-examination brought about by the film’s presentation of the ordinary and the violence of the everyday. This reading contrasts, though perhaps sometimes complements, the “hermeneutics of suspicion” seen to characterize critical textual analysis, and recasts, uncomfortably sometimes, the political, from something to be uncovered to something of which we are constitutive.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.028
Scholarly communication0.0100.009
Open science0.0010.003
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0030.000

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 head0.121
GPT teacher head0.392
Teacher spread0.271 · 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 designTheoretical or conceptual
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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