Individuals' favorite songs' lyrics reflect their attachment style
Bibliographic record
Abstract
Abstract Recent studies suggest that one's personality relates to their music preferences. Separately, research from an attachment theory perspective has demonstrated that attachment security and insecurity are important relationship‐related individual differences. We combined these two lines of inquiry here by investigating whether the lyrics of individuals' favorite songs about relationships reflect their attachment styles and related Big Five personality traits (Study 1; NParticipants = 469, NSongs = 4853). Individuals higher in attachment avoidance preferred relationship songs with lyrics expressing an avoidant attachment style, whereas individuals higher in neuroticism preferred relationship songs with lyrics expressing more attachment anxiety. We extended these results in a second study, finding that the lyrics of Western culture's 823 most popular songs from 1946 to 2015 mirrored societal trends of increasing social disengagement (i.e., were increasingly higher in attachment avoidance themes), suggesting that song lyrics impart psychological meaning at the sociocultural level as well. Our data therefore suggests that higher levels of attachment avoidance are reflected in preferred lyrics in relationship songs at both an individual and societal level.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".