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Record W1972318349 · doi:10.3138/md.49.2.188

The Ghost in the Machine: Heiner Müller’s Devouring Melancholy

2006· article· en· W1972318349 on OpenAlexvenueno aff
Kirk Williams

Bibliographic record

VenueModern Drama · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAmbivalenceObject (grammar)MetaphorArtSubject (documents)LiteratureHistoryAestheticsPsychoanalysisPsychologyPhilosophyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

Eating is a kind of memorialization, at least according to Freud, who exerts his own influence on Müller’s text. To take the lost object into oneself, cannibalizing and consuming it through ritual or metaphor, is one way that the subject masters the potentially paralysing ambivalence of loss. The dead live on, but they do not return; eating the dead, to paraphrase Müller, allows us to know them and be finished with them at the same time. The dead, however, are hard to keep down — they keep coming back up, rather like history itself. It is, as Hamletmachine illustrates, no small task to rid oneself of the literary past. Memory returns, unbidden, ghosts walk among the ruins, cycles of death and regeneration cannot be arrested by will or art.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.299

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)0.0000.000

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 head0.018
GPT teacher head0.210
Teacher spread0.192 · 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 designObservational
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

Citations3
Published2006
Admission routes1
Has abstractyes

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