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Record W1936149647

The ends of adaptation: comparative media, digital culture, and performance

2015· dissertation· en· W1936149647 on OpenAlexfundno aff
Nico Dicecco

Bibliographic record

VenueSummit (Simon Fraser University) · 2015
Typedissertation
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
FundersSimon Fraser UniversityCurtin University of Technology
KeywordsAdaptation (eye)Digital mediaComputer scienceBiologyWorld Wide WebNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

The starting point of this dissertation is a history of ideas tacitly organized around the conception of adaptation as a formal object-which is to say as a specific kind of intertext defined by its incorporation of material drawn from one or more precursor works.Within this framework, scholars have struggled against a set of recurrent methodological pitfalls having to do with the relative importance of medium specificity, the place and purpose of aesthetic evaluation, and the perennial reappearance of that critical bugbear, fidelity.Recognizing that the blanket acceptance or rejection of these concepts has so far done little to curb the problems associated with them, I argue in favour of treating these conceptual sticking points as symptoms of a more basic problem: the formal model of adaptation itself.In response, I make a case for shifting critical focus away from what adaptations as cultural objects are to what adaptation as a cultural discourse does.Accordingly, my approach in this project is primarily meta-critical and methodological.I lead with an analysis of the intellectual history that centralized an ontological definition of adaptation and maintained its basic assumptions even as post-structuralist thought and sociological inquiry began to influence the field.As this analysis proceeds, however, my attention increasingly moves towards articulating a performative model of adaptation, which turns around the idea that what makes adaptations adaptations is not inherent in any given object; it is generated as part of the cultural work performed through identifying one text with another, in contexts of production as much as in the processes of reception.In developing this model, I explore how it accounts for the role of desire in the recurrence of fidelity discourse, the (non)literal materiality of adaptations, the shifting mediascapes of digital culture, and the embodied work of interpreting adaptation as such.

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)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.009
Science and technology studies0.0150.050
Scholarly communication0.0280.025
Open science0.0020.014
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.035
GPT teacher head0.226
Teacher spread0.190 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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