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Record W2923283060 · doi:10.1177/1048291118824872

Breaking Point: Violence Against Long-Term Care Staff

2019· article· en· W2923283060 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNEW SOLUTIONS A Journal of Environmental and Occupational Health Policy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of Windsor
FundersUniversity of Stirling
KeywordsTerm (time)Long-term carePoint (geometry)Medical emergencyNursingMedicinePsychologyPhysics

Abstract

fetched live from OpenAlex

Direct resident care in long-term care facilities is carried out predominantly by personal support workers and registered practical nurses, the majority of whom are women. They experience physical, verbal, and sexual violence from residents on a regular basis. To explore this widespread problem, fifty-six staff in seven communities in Ontario, Canada, were consulted. They identified such immediate causes of violence as resident fear, confusion, and agitation and such underlying causes as task-driven organization of work, understaffing, inappropriate resident placement, and inadequate time for relational care. They saw violence as symptomatic of an institution that undervalues both its staff and residents. They described how violence affects their own health and well-being-causing injuries, unaddressed emotional trauma, job dissatisfaction, and burnout. They outlined barriers to preventing violence, such as insufficient training and resources, systemic underfunding, lack of recognition of the severity and ubiquity of the phenomenon, and limited public awareness.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.022
GPT teacher head0.349
Teacher spread0.327 · 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