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Record W3172979009 · doi:10.1177/02654075211018513

Adult attachment and engagement with fictional characters

2021· article· en· W3172979009 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Social and Personal Relationships · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyCharacter (mathematics)Attachment theoryNarrativeInterpersonal communicationSocial psychologyIdentification (biology)Developmental psychologyLiteratureArt

Abstract

fetched live from OpenAlex

Adult attachment influences how people engage with stories, in terms of how immersed or transported they become into these narratives and the tendency to form close bonds with characters. This likely stems from the ability of stories and story characters to provide interpersonal intimacy without the threat of rejection. In Study 1, we expand on this work to examine how attachment relates to two previously uninvestigated aspects of character engagement: character identification and parasocial interactions. Taking a statistically conservative approach, controlling for broader traits, we demonstrate that the attachment dimensions of anxiety and avoidance differentially predict these forms of character engagement. A high-powered, pre-registered, Study 2 follows up on these results by examining the types of characters that are most appealing, based on one's attachment orientation. Together, these studies demonstrate that attachment plays an essential role in both how we engage with characters and the types of characters to whom we are attracted.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.121
GPT teacher head0.297
Teacher spread0.176 · 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