MétaCan
Menu
Back to cohort
Record W2085561753 · doi:10.12968/jpar.2013.5.9.508

Violence in the workplace: implementing the Instant Aggression Model

2013· article· en· W2085561753 on OpenAlexaff
I.H.J. Bourne

Bibliographic record

VenueJournal of Paramedic Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsImpact
Fundersnot available
KeywordsAggressionEmergency Care PractitionerCombat Medical TechnicianPsychologyInterpersonal communicationPanicInstantState (computer science)Social psychologyAnxietyPsychiatryComputer sciencePedagogyContinuing professional development

Abstract

fetched live from OpenAlex

Paramedics, by the nature of their work, often enter into unknown, critical and sometimes hostile situations. Danger can emanate from the patient, particularly if they are confused, in a state of panic, inebriated or psychotic, from friends and family, work colleagues, or from members of the public. In such situations the best advice is undoubtedly to withdraw and summon support. This paper, however, addresses those situations where that is either not possible or appropriate. A model for understanding aggression as it unfolds is offered together with an examination of the interpersonal defusing and de-escalating skills.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.371
Teacher spread0.344 · 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 designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Paramedic PracticeSame topicWorkplace Violence and BullyingFrench-language works237,207