The threat simulation theory in light of recent empirical evidence: A review
Bibliographic record
Abstract
The recently proposed threat simulation theory (TST) states that dreaming about threatening events has a biological function. In the past few years, the TST has led to several dream content analysis studies that empirically test the theory. The predictions of the TST have been investigated mainly with a new content analysis system, the Dream Threat Scale (DTS), a method developed for identifying and classifying threatening events in dreams. In this article we review the studies that have tested the TST with the DTS. We summarize and reevaluate the results based on the dreams of Finnish and Swedish university students, traumatized and nontraumatized Kurdish, Palestinian, and Finnish children, and special dream samples, namely recurrent dreams and nightmares collected from Canadian participants. We sum up other recent research that has relevance for the TST and discuss the extent to which empirical evidence supports or conflicts with the TST. New evidence and new direct tests of the predictions of the TST yield strong support for the theory, and the TST's strengths seem to outweigh its weaknesses.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".