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Record W4376058153 · doi:10.24908/lhps.v1i1.15478

Ghosts Without Unfinished Business

2022· article· en· W4376058153 on OpenAlexaff
Abigail Egger

Bibliographic record

VenueLiving Histories A Past Studies Journal · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLiminalityAnimationSocial lifeAestheticsSocial relationshipPerceptionSociologyTrophyDead bodySocial mediaDigital eraConstruct (python library)Visual artsArtHistoryPsychologySocial psychologyAnthropologyThe InternetComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Historians have long written about the relationship between the living and the dead and the role ghosts play in maintaining this relationship. However, only recently have scholars turned to the ways death in the digital age has disurpted our traditional mourning rituals."Ghosts Without Unfinished Business: Recorded Media and the Liminal in Para-Social Mourning" explores the ways recording technology have shaped Western society's relationship with the dead from the development of the camera to the recent animation capabilities of CGI and "deep fake" technology. In particular, recordings construct a liminal space between life and death by altering our perceptions of the body, ghosts, and time, particularly when the relationship between the living and dead was para-social. This new mourning, theorized as para-social mourning, disrupts traditional understandings of ghosts as recordings are unchanging and frozen in time, thus disallowing the relationship between the living and dead to change. This paper concludes with a parallel drawn between the anxities between the development of the camera and the current anxities regarding CGI.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.040
GPT teacher head0.240
Teacher spread0.201 · 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.

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 routes1
Has abstractyes

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