Strong but insecure: Examining the prevalence and correlates of insecure attachment bonds with attachment figures
Bibliographic record
Abstract
This study examined whether people can be insecurely attached to figures who are actively sought out (and not just desired) to fulfill attachment functions and whether this has negative consequences for psychological well-being. A total of 122 participants rated 3–15 relational targets on measures including the extent to which the target fulfills important attachment functions and the attachment style characterizing the relationship. Participants also completed general measures of well-being and attachment style. We specifically focused on targets who could be classified as attachment figures based on the WHOTO and examined the attachment style characterizing these relationships. Results show that a significant proportion of attachment bonds can be characterized by insecurity, which has consequences both for the extent to which these attachment figures can fulfill important attachment functions and for overall well-being. The discussion considers the implications of these results for attachment priming research and the distinction between attachment strength and security.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".