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Record W3112923234 · doi:10.4000/tvseries.4982

Conceptualizing Otherness with Lost: Foucault, Lacan, and the Mediation of the Gaze

2016· article· en· W3112923234 on OpenAlexaff
Louis-Paul Willis

Bibliographic record

VenueTV/Series · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsGazeNarrativeSubjectivityPlot (graphics)MediationPanopticonExpression (computer science)AestheticsPsychoanalytic theoryEpistemologySociologyPsychoanalysisPsychologyPhilosophyLiteratureArtAnthropologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Among the numerous references to philosophy that permeate its narrative universe, Lost seems to be predominantly traversed by Foucauldian themes, mostly related to articulations of looking dynamics and surveillance. Themes related to panopticism and discipline constitute notable underpinnings for the series’ plot, as several previous analyses have pertinently demonstrated. This article proposes an examination of the spectatorial repercussions related to this facet of Lost, most importantly by establishing ties between the panoptic gaze and the gaze in its psychoanalytic conception, elaborated by Jacques Lacan. By examining both these concepts of a gaze deployed around the position of the Other, this article focuses on the series’ exploration of subjectivity in the era of panopticism. By exploring the importance and narrative deployment of these notions of the gaze within Lost, it is suggested that the series articulates a certain radicality around the notion of Otherness, as well as its expression through the televisual mediation of the gaze.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0100.078
Scholarly communication0.0120.010
Open science0.0020.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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