Bibliographic record
Abstract
According to Statistics Canada, eight million adults will be over the age of 65 by 2031, nearly 25 percent of the population. Increasingly, older adults report being victims of abuse, even though Canada has actively addressed the problem since the early 1980s (Podnieks, 1989). This presentation describes the most recent study to quantify the extent of elder abuse and neglect in Canada (McDonald, 2016). More than three quarters of a million Canadian elders suffered some form of abuse last year, more than double the 1998 finding. One reason could be a rise in financial abuse, the second most frequent form behind psychological abuse. The most important risk factor was depression, followed by having been abused in another stage of the life course. This presentation describes the study’s guiding theoretical framework, methodology, and findings and draws conclusions and offers implications for future research and services for maltreated older adults in Canada.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.040 | 0.012 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".