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Record W4285035981 · doi:10.22215/etd/2022-15033

Literapolis: The Post-Internet Textual City

2022· dissertation· en· W4285035981 on OpenAlexaff
Daniel Dickson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsReading (process)Agency (philosophy)The InternetNarrativeCode (set theory)SociologyMedia studiesLinguisticsGeographyHistoryWorld Wide WebArtLiteratureComputer scienceSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Literapolis' reconceives the post-Internet city towards advocating the textual production of its citizens.It reacts to the precarious agency, accessibility, and heterogeneity caused by disenfranchising screen environments.In response, the thesis frames the city as a 'born-digital living literary,' whose spaces of writing and reading, though obfuscated, remain tied to place.The thesis unrolls over five scrolls.The first examines primary terms.The second organises five nested spatio-textual scales -code, page, codex, archive, and city -and relates interdisciplinary research to propose the scales' structural re-definition.The third develops a methodology of vectors, points, and fields to apply the scales to an epicentral post-Internet case study: San Francisco.The fourth posits Literapolis citizen narrative virtualities to re-enfranchise a vital living literary.The fifth reflects on the Literapolis as a language and ethic for reading the city, specifies how research might expand beyond Silicon Valley, and enacts a spatio-text.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0110.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.016
GPT teacher head0.318
Teacher spread0.302 · 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
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

Citations1
Published2022
Admission routes1
Has abstractyes

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