Bibliographic record
Abstract
Abstract Elder abuse (EA) has been recognized as a serious public health concern. Recent studies have found that approximately 10% of community-dwelling, cognitively intact older adults experience some form of EA each year. Although EA research has made substantial progress, EA is often under-reported, with only an estimated 15% of cases being reported to formal support services. One of the main reasons for the under-reporting of EA is the victims’ feelings of shame, which have been shown to be exacerbated when the perpetrator is a family member and/or an individual with whom the older adults have close trusting relationships. Qualitative interviews conducted with 12 older adult (parent) and adult child caregiver dyads (n=24) revealed that older adults who experience EA by their adult children experience intense shame. Thematic analysis focused on what led to these feelings of shame, and this resulted in four main themes: (1) Failure in their role as a parent; (2) Adult children viewing them as powerless and unworthy; (3) Experiencing negative psychological effects; and (4) Self-blame. With a sense of responsibility to protect their family, older adults tend to keep ‘family shame’ to themselves, leading to a reluctance to disclose EA. As spouses and adult children, the two most common caregiving types, have also been reported to be the two most common groups of EA perpetrators, gaining a better understanding of the root causes of shame can help to support older adults in living safely in their homes and communities for as long as possible.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".