How many factors does the sense of community index assess?
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.
Bibliographic record
Abstract
Abstract Studies of university students’ sense of community (SOC) use various scales, one of which is the widely used Sense of Community Index (SCI), conceptualized as a 4‐factor model: membership, influence, needs fulfillment, and shared emotional connection. Research has been unable to show a reliable 4‐factor solution. One possible explanation may be that negatively worded items contribute to lack of model fit, which would be consistent with the claim that SOC was conceptualized as a unipolar positive construct. Data were collected using a positively worded SCI ( N = 794). Four models were tested with confirmatory factor analysis in structural equation modeling: 1‐factor, theorized four‐factor, revised 3‐factor, and revised 4‐factor. None of the models showed good fit, though the fit of the 1‐factor model was improved over the 4‐factor. More studies are needed to attempt replication with a positively worded SCI.
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 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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.010 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it