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Record W4243658701 · doi:10.32920/ryerson.14655513

Effects of cooperative and competitive game playing on empathy

2021· preprint· en· W4243658701 on OpenAlexaff
Nicole Charewicz

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsToronto Metropolitan UniversityOntario Tech University
Fundersnot available
KeywordsEmpathyPsychologySocial psychologyPerceptionProsocial behaviorVideo gameComputer scienceMultimedia

Abstract

fetched live from OpenAlex

<p>The present study examined the effects of cooperative and competitive game playing on empathy. Participants were randomly assigned to one of two conditions, with a confederate: playing a video game cooperatively (N = 51), or playing a video game competitively (N = 55). The game played was the non-violent, puzzle-platformer Portal 2. When playing cooperatively, participants completed levels through the multiplayer option where they had to act together with the confederate to be successful. In the competitive condition participants played the single-player campaign and competed with the confederate for the best time-to-completion of the first series of levels. After playing Portal 2 for approximately 15 minutes, participants watched the confederate submerge her hand in what they thought was ice-cold water for 30 seconds. Participants sat facing the confederate and rated their perception of the confederate’s pain, their own pain, the amount of empathy they felt for the confederate, as well as how close they felt to the confederate. A subsequent measure also assessed the extent of participants’ empathic concern by providing them the option to reduce the time that the confederate had to put her hand in the water a second time. Results showed no significant differences between the two conditions with respect to levels of empathy. However, participants felt more trusting and friendly towards the confederate in the cooperative condition.</p>

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)0.000
metaresearch head score (Gemma)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

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)0.0010.000

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 head0.036
GPT teacher head0.275
Teacher spread0.239 · 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 designQualitative
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

Citations0
Published2021
Admission routes1
Has abstractyes

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