Bibliographic record
Abstract
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.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 source (direct Gemma or distilled Codex), 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".