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Record W4282978303 · doi:10.1093/geront/gnac083

RISE: A Conceptual Model of Integrated and Restorative Elder Abuse Intervention

2022· article· en· W4282978303 on OpenAlex
David Burnes, Marie‐Therese Connolly, Erin Salvo, Patricia Kimball, Geoff Rogers, Stuart Lewis

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Gerontologist · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of Toronto
FundersAdministration for Community LivingU.S. Department of Health and Human Services
KeywordsIntervention (counseling)Goal Attainment ScalingRestorative justiceDyadMotivational interviewingPerspective (graphical)PsychologyModalitiesConceptual modelEconomic JusticeConceptual frameworkApplied psychologyCriminologySocial psychologyPsychiatryPolitical scienceSociologyComputer science

Abstract

fetched live from OpenAlex

Despite a growing number of elder abuse (EA) cases nationwide, response programs such as adult protective services (APS) lack a defined, prolonged intervention phase to address these complex situations. This article presents RISE, a model of EA intervention that works alongside APS or other systems that interact with at-risk older adults. Informed by an ecological-systems perspective and adapting evidence-based modalities from other fields (including motivational interviewing, teaming, restorative justice, and goal attainment scaling), the RISE model intervenes at levels of the individual older adult victim, individual harmer, their relationship, and community to address EA risk and strengthen systems of support surrounding the victim-harmer dyad. The RISE model addresses an intervention gap in existing systems to better meet the needs of EA victims and others in their lives, leading to more sustainable outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.333
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it