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Record W3175338865 · doi:10.29173/irie176

Handbook of computer game studies

2005· article· en· W3175338865 on OpenAlexvenueno aff
Michael Nagenborg

Bibliographic record

VenueThe International Review of Information Ethics · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsFocus (optics)Computer gameField (mathematics)Computer scienceMedia studiesLibrary scienceOperations researchMultimediaSociologyEngineering

Abstract

fetched live from OpenAlex

Review of Joost Raessens and Jeffrey Goldstein: Handbook of computer game studies. Cambridge, Massachusetts – London, England: MIT Press 2005. By more than 450 large-format pages the publishers offer a view of current research in the field of “game studies”. With almost no exception, the 27 articles are of high quality. Readers, however, who are familiar with the works of the single authors are offered only little new information. Unfortunately, the authors mostly focus on western, particularly US-American games and players. But still the book can be recommended both as a consolidating introduction and a textbook.

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)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0350.021

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 head0.080
GPT teacher head0.415
Teacher spread0.335 · 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

Citations292
Published2005
Admission routes1
Has abstractyes

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