MétaCan
Menu
Back to cohort
Record W2099005400 · doi:10.7202/007302ar

Multiple Risk Factors for Violence to Seven Occupational Groups in the Swedish Caring Sector

2003· article· en· W2099005400 on OpenAlexvenueno aff
Eija Viitasara, Magnus Sverke, Ewa Menckel

Bibliographic record

VenueRelations industrielles · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadOccupational safety and healthNursingWelfareWorkplace violenceHealth carePsychologyMedicineHuman factors and ergonomicsFamily medicineEnvironmental healthPoison controlPolitical science

Abstract

fetched live from OpenAlex

Violence towards health-care personnel represent an increasing problem, but little is known in terms of how different occupational groups are affected. A questionnaire was sent to a stratified sample of 2,800 of 173,000 employees in the Swedish municipal health and welfare sector. Seven major groups working with the elderly or persons with developmental disabilities were considered: administrators, nursing specialists, supervisors, direct carers, nursing auxiliaries, assistant nurses, and personal assistants. The response rate was 85 percent. Fifty-one percent of respondents reported exposure to violence or threats of violence over one year. The most vulnerable groups were assistant nurses and direct carers (usually of the developmentally disabled). Individual characteristics, such as age and organizational tenure, were related to exposure. Work-related characteristics, such as type of workplace, working full-time with clients, organizational downsizing, and high workload, were also associated with risk. Greater knowledge of impacts on different professional groups and relevant prevention are required.

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 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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.303
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueRelations industriellesSame topicWorkplace Violence and BullyingFrench-language works237,207