Impact of the recession / by Duncan M. Shields. --
Bibliographic record
Abstract
Over the last few years, Canada and many other \nindustrialized nations have been facing serious \neconomic and fiscal crises. There is some evidence \nindicating that this kind of economic contraction is a \nsignificant source of psychosocial stress, and that \nduring times of economic recession or uncertainty a \nrelationship exists between economic events and \nmeasures of health and well being at both the \nindividual and societal level. \nAn exploration of the nature and strength of any \nsuch relationship is important in identifying \nindividuals that may be at high risk due to economic \ncontraction, and to identify what factors may buffer \nagainst the negative effects of recession. The present \nstudy was designed to assess the impacts of the current \neconomic recession on a university student population. \nIn addition to the exploratory aspect of this study, \nthe relationship between economic events and depression \nand hopelessness was investigated within the framework \nof self-efficacy theory. \nThe specific objectives were: to evaluate the relative contributions of domain specific (economic) \nself-efficacy, general self-efficacy, and outcome \nexpectations in the determination of depression and \nhopelessness; and to investigate students' perceptions \nof the impact of economic recession on themselves and \nother students. \nPath analyses showed that depression was more \nstrongly associated with beliefs about one's selfefficacy \nin general, while feelings of hopelessness \nwere more strongly related to beliefs about personal \ncontrol over economic issues. Outcome expectations \nwere found to have no additional predictive value in \nunderstanding depression and hopelessness scores. \nThese findings support the role of cognitive processes \n(self-efficacy beliefs) in the mediation of the effects \nof stressors such as negative economic events on mental \nhealth.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".