Development and validation of a measure of social well-being during doctoral studies: The sense of scientific community scale
Bibliographic record
Abstract
Several qualitative studies suggest that the sense of belonging to the scientific community is critical to the success of the doctoral journey. Although a few tools have been developed to capture some components of the sense of scientific community, no instrument is available to measure this construct in its entirety. The purpose of this study was to develop the Sense of Scientific Community Scale (SSCS) and to examine its psychometric qualities using a sample of 318 doctoral students in Canada. Five indicators of construct validity (exploratory, confirmatory, discriminant, predictive, and concurrent) and three indicators of reliability (internal consistency, test-retest and temporal stability) of the SCSS were examined. In sum, this scale comprises 18 items divided into three factors (perception of belonging, influencing, and benefiting from support) providing good internal consistency indices. The psychometric qualities of the SCSS justify its use in future studies.
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How this classification was reachedexpand
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 | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".