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Record W4366822975 · doi:10.1177/27538702231170132

Collaborative projection and the twin ecstasies of DIY cineworlding

2023· article· en· W4366822975 on OpenAlexaff
Michael B. MacDonald

Bibliographic record

VenueDIY Alternative Cultures & Society · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsMacEwan University
Fundersnot available
KeywordsCapitalismNormativeSociologyEthnographyPsychoanalytic theoryCitizenshipProjection (relational algebra)Production (economics)AestheticsOrder (exchange)EpistemologyMedia studiesPolitical scienceArtComputer scienceAnthropologyPhilosophyLawPoliticsBusinessPsychologyEconomicsPsychoanalysis

Abstract

fetched live from OpenAlex

The notion that ethnographic practice needs to be normative in order to be rigorous is problematic, especially when the partners in that research are producing experimental and resistant DIY cultures. Nonnormative ethnographers are “activist” in their critical engagement with dominant regimes of truth and must contend with digital disruption and platform capitalism that has vastly expanded DIY production. It is no longer possible to identify DIY culture with self-production because digital self-production is simply demanded for the “digital citizenship” of platform capitalism. In this article, the psychoanalytic concept of projection is turned upside down and understood as a socially performed digital-bodying that worlds. The screen becomes a location of dissensus, projecting the ecstatic truth of Modern/capitalist worldings or Altermodern/anti-capitalist worldings. Cinematic research-creation, CineWorlding, is an activist cinematic posthumanographic study of the interstices that infold concepts, bodies, social, technological, and environmental ecologies into worldings.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.027
Scholarly communication0.0090.009
Open science0.0010.010
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.275
Teacher spread0.248 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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