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Record W2808803555 · doi:10.1177/2050157918770696

Attached to dating apps: Attachment orientations and preferences for dating apps

2018· article· en· W2808803555 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMobile Media & Communication · 2018
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyAttachment theoryPreferential attachmentOrientation (vector space)Social psychologyWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Our study examines attachment-related differences in the use of dating applications (dating apps). We collected online survey data regarding people’s attachment orientation and dating app preferences. People with a more anxious attachment orientation were more likely to report using dating apps than people lower in anxious attachment; people with a more avoidant attachment orientation were less likely to report using dating apps than people lower in avoidant attachment. Participants who used dating apps cited Tinder, OkCupid, and Plenty of Fish as those most commonly used. The most common reason people reported for using apps was to meet others, and the most common reason people reported for not using apps was difficulty trusting people online. Our findings suggest that individual differences in attachment may be relevant for understanding online behavior, and that dating apps might be a fruitful avenue for future research on attachment-related differences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.091
GPT teacher head0.428
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it