Bibliographic record
Abstract
Our study investigated earworms in relation to affect. An earworm is defined as hearing music without currently listening to music. Affect refers to emotions. As the research on earworms is limited, one goal of our study was to confirm and advance prior findings, such as whether or not neuroticism is associated with a heightened occurrence of earworms. We hypothesized that earworms are a type of ruminative thought, which are typically associated with stress and worry. Based on this hypothesis, our specific prediction was that people with higher levels of stress/anxiety would be more likely to experience earworms. To test this prediction, we collected self-report measures from undergraduate students enrolled at MacEwan University. In part one of the study, participants filled out a questionnaire regarding music experience and importance, personality (to assess trait anxiety), and affect (to assess state anxiety). Personality was measured with the Big 5 Inventory (BFI-2-S). A modified positive and negative affect schedule (PANAS) was used to measure affect. For part two, participants filled out the PANAS questionnaire whenever they had an earworm throughout the semester. On two random occasions, participants received an email to fill out the PANAS questionnaire regardless of earworm occurrence. We expect that those who report more earworms throughout the semester will have corresponding higher ratings of stress/anxiety on the modified PANAS and higher ratings of neuroticism on the BFI-2-S. Our research posits reasons for the occurrence of earworms and may support the idea that stress-reduction measures can reduce negative earworm experiences. Faculty Mentor: Michele Moscicki Department: Psychology (Honours)
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".