Information practices in coopetition context: the case of a large video game company
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.009 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".