Can You Tell That I’m in a Relationship? Attachment and Relationship Visibility on Facebook
Bibliographic record
Abstract
People often attempt to shape others' perceptions of them, but the role of romantic relationships in this process is unknown. The present set of studies investigates relationship visibility, the centrality of relationships in the self-images that people convey to others. We propose that attachment underlies relationship visibility and test this hypothesis across three studies in the context of Facebook. Avoidant individuals showed low desire for relationship visibility, whereas anxious individuals reported high desired visibility (Studies 1 and 2); however, similar motives drove both groups' actual relationship visibility (Study 1). Moreover, both avoidant individuals and their partners were less likely to make their relationships visible (Studies 1 and 3). On a daily basis, when people felt more insecure about their partner's feelings, they tended to make their relationships visible (Study 3). These studies highlight the role of relationships in how people portray themselves to others.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".