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Record W4380046922 · doi:10.1016/j.heliyon.2023.e17066

Development and validation of a questionnaire (GHOST) to assess sudden, unexplained communication exclusion or “ghosting"

2023· article· en· W4380046922 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

VenueHeliyon · 2023
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGhostingPsychologyMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The topic of "ghosting" as a method of terminating a relationship has been discussed in both popular media and academic circles. Although research on this issue is scarce, the concept has acquired popularity and gained scholarly attention. A reliable and valid measure of this phenomenon does not, however, exist. GHOST (The Ghosting Questionnaire) was designed and psychometrically tested to explore ghostee experiences. A total of 811 adults participated in an online survey to test this instrument. It was developed based on a thorough analysis of research on the topic of ghosting using a phenomenological qualitative method to identify ghosting domains and generate questionnaire items. In terms of content validity and construct validity, the final version of the measure was found to be satisfactory. GHOST was found to have adequate internal consistency - scores of 0.74, 0.74, and 0.80, indicating acceptable Cronbach's alpha, McDonald's omega, and ordinal's alpha coefficients, respectively. Factor analyses found the GHOST questionnaire to be a valid and reliable instrument that can be used for screening ghosting experiences and for designing community-based distress prevention and intervention programs. A dynamic fit index (DFI) cutoffs approach was also used and showed robust fitting.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.371
Teacher spread0.273 · 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