Negative self-synchronization: Will I change to be like you when it is bad for me?
Bibliographic record
Abstract
The current research examined whether people will attempt to modify internal aspects of the self to make them congruent with others, even when those modifications have negative implications for the self, a phenomenon we refer to as negative self-synchronization. We proposed that negative self-synchronization will occur only for individuals who are securely attached. Across 4 experiments, participants who were high in secure attachment were more likely than those low in attachment security to engage in negative self-synchronization (Experiments 1-4). Attachment style did not moderate positive self-synchronization (Experiments 1 and 2). In addition, priming secure attachment increased negative self-synchronization among insecure participants (Experiments 2 and 3). Conversely, priming insecure attachment decreased negative self-synchronization among secure participants (Experiment 4). Implications of these findings for social synchronization processes, the need to belong, and attachment security are discussed.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".