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Record W4313169900 · doi:10.47989/irisic2232

Information practices in coopetition context: the case of a large video game company

2022· article· en· W4313169900 on OpenAlexaboutno aff
Joanne du Hommet, Madjid Ihadjadène, Luc Grivel

Bibliographic record

VenueInformation Research an international electronic journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge managementCoopetitionContext (archaeology)Exploratory researchTypologyGrounded theoryInformation seekingInformation systemInformation managementInformation sharingInformation source (mathematics)MarketingQualitative researchBusinessComputer scienceSociologyWorld Wide WebGame theoryInformation retrieval

Abstract

fetched live from OpenAlex

Studies on the information practices in a cooperative context are rare. Yet, issues of access, sharing or retention of information are crucial. This study investigates how professionals in a global digital entertainment company define their information source horizon and the factors that influence them. Using Savolainen’s information horizon methodology, we conducted an exploratory study based on interviews organised at the Montreal studio during which our 29 participants had to place their sources of information on mind maps. Quantitative data was collected and analysed on participants' preferences for information sources. We also employed grounded theory techniques to review our interview transcripts using NVivo software. We propose a new categorisation of sources and confirm the typology of Savolainen’s criteria. The results revealed that coopetition and technological contexts shaped information practices of gameworkers. The results of our study on the informational practices of gameworkers could find application in strategic information and knowledge management.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.009
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.423
Teacher spread0.379 · 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 designNot applicable
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

Citations2
Published2022
Admission routes1
Has abstractyes

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