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Record W145404863 · doi:10.11575/prism/5464

Coded territories: tracing indigenous pathways in new media art

2014· book· en· W145404863 on OpenAlexvenueaboutno aff
Kerry Swanson

Bibliographic record

VenueLibraries and Cultural Resources (University of Calgary) · 2014
Typebook
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingIndigenousGovernment (linguistics)The artsLibrary sciencePolitical sciencePublic administrationMedia studiesSociologyLawComputer scienceBiology

Abstract

fetched live from OpenAlex

This collection of essays provides a historical and contemporary context for Indigenous new media arts practice in Canada. The writers are established artists, scholars, and curators who cover thematic concepts and underlying approaches to new media from a distinctly Indigenous perspective. Through discourse and narrative analysis, the writers discuss a number of topics ranging from how Indigenous worldviews inform unique approaches to new media arts practice to their own work and specific contemporary works. With contributions by: Archer Pechawis, Jackson 2Bears, Jason Edward Lewis, Steven Foster, Candice Hopkins, and Cheryl L'Hirondelle. The book was created in partnership with ImagineNATIVE Film and Media Arts Festival.

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)0.002
metaresearch head score (Gemma)0.005
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: Other
Teacher disagreement score0.248
Threshold uncertainty score0.498

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0190.028
Scholarly communication0.0140.007
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.019
GPT teacher head0.152
Teacher spread0.133 · 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

Citations18
Published2014
Admission routes2
Has abstractyes

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