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Record W6889026374 · doi:10.25384/sage.c.6278197

The UBC State Social Connection Scale: Factor Structure, Reliability, and Validity

2022· other· en· W6889026374 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFeelingScale (ratio)Connection (principal bundle)State (computer science)Social relationPower (physics)Social researchExploratory factor analysis

Abstract

fetched live from OpenAlex

Social connection plays a central role in people’s everyday lives. Although researchers have traditionally focused on the benefits of experiencing an enduring sense of social connection, recent research has also begun to explore the contextual factors that shape momentary feeling of social connection. To date, however, no psychological scales have been developed to measure state social connection. To address this gap, we developed the 10-item UBC State Social Connection Scale (UBC-SSCS). In Study 1, we generated and refined our initial pool of items and confirmed our hypothesized factor structure in a large university sample. In Studies 2 to 3, we established several forms of validity. We provide foundational evidence that the UBC-SSCS is a reliable and valid instrument for assessing momentary feelings of social connection. Our exploratory findings also suggest that researchers can substantially increase their statistical power using state (vs. trait) measures to capture fluctuations in feelings of social connection.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.076
GPT teacher head0.343
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueSage Journals DataFrench-language works237,207