MétaCan
Menu
Back to cohort
Record W4229455388 · doi:10.29173/pathfinder57

Indigenous Video Games in Libraries

2022· article· en· W4229455388 on OpenAlexaffvenue
Candie Tanaka

Bibliographic record

VenuePathfinder A Canadian Journal for Information Science Students and Early Career Professionals · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIndigenousContext (archaeology)Video gameDiversity (politics)StudioCreativityRepresentation (politics)Presentation (obstetrics)MultimediaMedia studiesComputer scienceSociologyPolitical scienceVisual artsHistoryPoliticsArtAnthropologyLaw

Abstract

fetched live from OpenAlex

There is a recent movement known as Indigenous Futurisms that examines Indigenous perspectives within the context of technology. In relation to this, video gaming continues to be one of the fastest growing forms of new media, yet diversity in the industry is still an issue. There is especially apparent with a lack of proper representation of Indigenous video game characters and Indigenous storylines. While this is starting to change with the recent rise of a handful of Indigenous owned gaming studios and creators, there are still challenges around accessibility for game play. Video games made by Indigenous creators or with Indigenous characters are for the most part non-existent in most public library collections. When we discuss decolonization in libraries, video games as a popular form of media are often overlooked and not viewed as valuable educational tools that encourage literacy and creativity. This paper suggests changes that can be made to ensure that video games that share Indigenous Knowledges and traditions or are made by Indigenous creators are made accessible and are represented in library collections and spaces.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0020.005
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.332
Teacher spread0.298 · 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 teacher head, not a consensus.

Study designObservational
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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuePathfinder A Canadian Journal for Information Science Students and Early Career ProfessionalsSame topicDigital Games and MediaFrench-language works237,207