Further evidence in support of the validity of the post-secondary student stressors index using a nationwide, cross-sectional sample of Canadian university students
Bibliographic record
Abstract
The Post-Secondary Student Stressors Index (PSSI) was created to facilitate improved evaluation of the sources of post-secondary student stress. This study reports evidence in support of the validity of the tool using a large, nationwide cross-sectional sample of students attending universities across Canada during the 2020-2021 academic year. We provide additional evidence for the construct validation of the PSSI, including internal structure evidence and relations to other variables by estimating multiple-indicator, multiple-cause models and investigating Spearman's rho correlation coefficients between the PSSI and like constructs. Based on index validation guidelines, results provide further support for the internal structure of the PSSI, demonstrating hypothesized relationships with like constructs and manifest variables, as well as acceptable goodness-of-fit statistics. Similarly, correlation coefficients were statistically significant and in line with directionality hypotheses. The results of this research provide further evidence for the validity of the PSSI among varied university student populations in Canada and addresses several of the limitations identified in earlier preliminary psychometric work on the instrument.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".