Особенности внутриличностного конфликта студенток высших учебных заведений
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
Children exposed to parental psychiatric disorders have an increased risk of several psychiatric disorders, impaired development, behavioural problems, injuries, physical illness and mortality. Even though this high-risk group has been shown to benefit from health promotion and preventive interventions, estimates of the size of the population at risk are not available. Estimating the number of exposed children using adult survey data will likely generate valuable information for health policy, planning, and advocacy. In this paper, the authors present a method to indirectly estimate the size of this population using secondary data. A Canadian adult health survey and the Census were combined to estimate the prevalence of exposure of children less than 12 years to parental and non-parental psychiatric disorders. A method to combine census and survey data is presented and tested under varying degrees of data availability. Results are compared to the actual number of children exposed to parental psychiatric disorders and discussed. The most accurate estimates were obtained when the most complete survey was combined with relatively detailed census information. Incomplete survey simulations produced substantial underestimates of the prevalence of exposure even when combined with detailed census information.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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