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Record W2279695079 · doi:10.3366/film.2016.0003

Real Images Flow: Mullā Sadrā Meets Film-Philosophy

2016· article· en· W2279695079 on OpenAlexaff
Laura U. Marks

Bibliographic record

VenueFilm-Philosophy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRealmPhilosophyEpistemologyAestheticsLiteratureArtHistoryArchaeology

Abstract

fetched live from OpenAlex

The eastern Islamic concept of the imaginal realm, which explains how supra-sensory realities present themselves to imaginative perception, can enrich the imagination of film-philosophy. The imaginal realm, in Arabic ‘alam al-mithal, world of images, or ‘alam al-khayal, imaginative world, is part of a triadic ontology of sensible, imaginal, and intelligible realms. Diverging from roots shared with Western thought in the concept of the imaginative faculty, the Islamic imaginal realm is supra-individual and more real than matter. The imaginal realm is a radically pro-image concept, affirming the importance of poetry, art, and images in motion. As developed by the Persian philosopher Sadr al-Dîn Muhammad al-Shîrâzî, known as Mullâ Sadrâ (1571–1640), the imaginal realm flows and intensifies, in a process philosophy we may fruitfully compare with Spinoza, Leibniz, and Whitehead. I sketch the genealogy of the imaginal realm and compare it to contemporary Western film-philosophy. I suggest how this transcendental concept can be made immanent. Finally, I draw from contemporary Muslim thinkers, such as Mohammed Arkoun, who ground a visionary collective politics in the imaginal realm. My central example, the documentary The Lebanese Rocket Society (2012) by Joana Hadjithomas and Khalil Joriege, exemplifies film's imaginal powers.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.016
Scholarly communication0.0090.007
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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

Citations30
Published2016
Admission routes1
Has abstractyes

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