The nightmare protection hypothesis: An experimental inquiry
Bibliographic record
Abstract
Using the ideas generated in Revonsuo and Valli’s Threat Simulation model of the function of dreaming, previous research looked at how military personal’s dreams were associated with video game play. A nightmare protection effect was found and replicated using an undergraduate student population. Based on the previous findings, in this study an experimental manipulation was conducted where male participants engaged in one of three computer tasks, including gaming and search. All participants also viewed a frightening movie clip. Following the laboratory session respondents were asked to report a dream. The Threat Simulation method of coding dreams was used to assess threat in participant’s dreams. The major hypothesis was that playing a combat centric game would be more likely to result in behaviors in the dream which were less nightmarish after seeing the frightening movie clip, relative to playing a creative video game or doing a computer search task. The results support the thesis for high end male gamers playing combat centric video games close in time to being exposed to a frightening film clip. These young men are either not perceiving the same danger in their follow-up dream as threatening or that the content is not as scary as those without a recent experience of combat centric gaming.
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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 | 0.013 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".