Bibliographic record
Abstract
HEALTH ISSUE: Depression causes significant distress or impairment in physical, social, occupational and other key areas of functioning. Women are approximately twice as likely as men to experience depression. Psychosocial factors likely mediate the risks for depression incurred by biological influences. KEY FINDINGS: Data from the 1999 National Population Health Survey show that depression is more common among Canadian women, with an annual self-reported incidence of 5.7% compared with 2.9% in men. The highest rates of depression are seen among women of reproductive age. Predictive factors for depression include previous depression, feeling out of control or overwhelmed, chronic health problems, traumatic events in childhood or young adulthood, lack of emotional support, lone parenthood, and low sense of mastery. Although depression is treatable, only 43% of depressed women had consulted a health professional in 1998/99 and only 32.4% were taking antidepressant medication. People with lower education, inadequate income, and fewer contacts with a health professional were less likely to receive depression treatment. DATA GAPS AND RECOMMENDATIONS: A better understanding of factors that increase vulnerability and resilience to depression is needed. There is also a need for the collection and analysis of data pertaining to: prevalence of clinical anxiety; the prevalence of depression band 12 months after childbirth factors contributing to suicide contemplation and attempts among adolescent girls, current treatments for depression and their efficacy in depressed women at different life stages; interprovincial variation in depression rates and hospitalizations and the impact and costs of depression on work, family, individuals, and society.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.168 | 0.056 |
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".