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Record W4328004621 · doi:10.47761/494a02f6.57291c4b

Film Review: Allegory and Its Interpretational Force in "mother!"

2018· article· en· W4328004621 on OpenAlexaff
Jonathan L. Wright

Bibliographic record

VenueInVisible Culture · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsYork University
Fundersnot available
KeywordsAllegoryArtLiterature

Abstract

fetched live from OpenAlex

Most critics agree that Darren Aronofsky's 2017 film mother!operates as some sort of allegory.There are a few different allegories to choose from, including the biblical narrative of creation, fall, and sacrifice; the act of artistic (or even cinematic) creation as consuming and oblivious; and the depletion of natural resources by human cultures.The winding plot of mother!will not be recounted here, since it both relies on the element of surprise and is so baroque that it would take the larger part of this review just to present it.At its core, the film depicts a woman experiencing a set of increasingly dramatic trials involving her house, her husband, and her newborn child, most of which seem entirely inexplicable except within the schema of an allegory or extended metaphor.The idea of a film as a representation of other, different events is not unique to mother!After all, "reading" a film through a psychoanalytic, feminist, Marxist, or (more recently) queer lens has been an accepted approach in academia for decades.Yet there is a difference in methodology between those readings and the reception of mother!Only the staunchest proponents of theoretical positions would argue that a film they are writing about cannot be experienced without their ideological frame.With mother!, however, there seems to be a consensus that experiencing the film outside of an allegorical understanding would be missing what the film is "about."

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.250
Teacher spread0.225 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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