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Record W4293696036 · doi:10.3138/topia-2021-0020

Loved to Death

2022· article· en· W4293696036 on OpenAlexaffvenue
Ricky Varghese

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPsychoanalysisMiddle classPsychologySociologyGender studiesLawPolitical science

Abstract

fetched live from OpenAlex

Some viewers of Michael Haneke’s award-winning film Amour (2012) may read it “simply” as a film about assisted dying. Here, I explore how Haneke attended to the experiences of aging and disability, and how these categories inform intimate relations, in this case that of an aging middle-class heterosexual couple living in Paris. As the deterioration of the body intensifies, what does it mean for love itself to intensify to the point of surrendering to the demand of subjecting the one you love to death. Thinking alongside the work of Sigmund Freud and Kaja Silverman, I ask after what may happen if and when love has the capacity to demand upon one the annihilation of their beloved. How is the beloved remembered, preserved, and forgotten as they age, and what might it mean to see love as not merely a cure but also a thing that has the capacity to kill?

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: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.011
Scholarly communication0.0060.005
Open science0.0000.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0110.002

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 head0.138
GPT teacher head0.299
Teacher spread0.161 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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