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Record W4392237758 · doi:10.1177/02762366241234017

Attitude Towards Dreams: Associated Factors

2024· article· en· W4392237758 on OpenAlex
Michael Schredl, Silvia Marin-Dragu, Ravishankar Subramani Iyer, Sandra Meier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImagination Cognition and Personality · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyPsychopathologyOpenness to experiencePersonalityCoping (psychology)Social psychologyPsychotherapistClinical psychology

Abstract

fetched live from OpenAlex

Representative surveys indicated that the attitude towards dreams varies greatly: some participants agreed to statements like “Dreams are random nonsense” but others expressed more positive attitudes that dreams might be beneficial. The present online study (N = 1,507 participants) elicited attitude towards dreams, personality (Big Five factors), current psychopathology, and COVID19-related worries. As expected, the present study showed that openness to experiences, but also current psychopathology and worries were associated with more positive attitudes towards dreams. This might indicate that persons with problems might turn to dreams, as they might be beneficial with coping those problems. Longitudinal studies might validate the idea that experiencing beneficial effects of dreams, for example, within a therapeutic setting, might affect the attitude towards dreams in a positive way. And, if persons with problems turn to dreams, it would be very helpful to include the tool of working with dreams in current psychotherapy practice.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.088
GPT teacher head0.369
Teacher spread0.281 · 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