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Record W2002531171 · doi:10.4018/jgcms.2011010105

Cognitive Ethnography

2011· article· en· W2002531171 on OpenAlex
Brock Dubbels

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Gaming and Computer-Mediated Simulations · 2011
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNarrativeEthnographyContext (archaeology)CognitionConstruct (python library)Video gameSociologyPsychologyEpistemologySocial psychologyComputer scienceAnthropologyLinguisticsMultimediaGeography

Abstract

fetched live from OpenAlex

This paper describes cognitive ethnography as a method of choice for game studies, multimedia learning, professional development, leisure studies, and activities where context is important. Cognitive ethnography is efficacious for these activities, as it assumes that human cognition adapts to its natural surroundings (Hutchins, 1995, 2010) with emphasis on analysis of activities as they happen in context; how they are represented; and how they are distributed and experienced in space. The methodology is described for increasing construct validity (Cook & Campbell, 1979; Campbell & Stanley, 1966) and the creation of a nomological network (Cronbach & Meehl, 1955). This description of the methodology is contextualized with a study examining the literate practices of reluctant middle school readers playing video games (Dubbels, 2008). The study utilizes variables from empirical laboratory research on discourse processing (Zwann, Langston, & Graesser, 1996) to analyze the narrative discourse of a video game as a socio-cognitive practice (Gee, 2007; Gee, Hull, & Lankshear, 1996).

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.061
GPT teacher head0.354
Teacher spread0.293 · 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