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Record W2944026602 · doi:10.1002/acp.3568

The Self‐Administered Witness Interview Tool (SAW‐IT): Enhancing witness recall of workplace incidents

2019· article· en· W2944026602 on OpenAlexafffund
Carla L. MacLean, Fiona Gabbert, Lorraine Hope

Bibliographic record

VenueApplied Cognitive Psychology · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsKwantlen Polytechnic University
FundersKwantlen Polytechnic University
KeywordsWitnessRecallPsychologyEyewitness memoryApplied psychologySchematicSocial psychologyQuality (philosophy)Cognitive psychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Summary Given the often crucial role of witness evidence in occupational health and safety investigation, statements should be obtained as soon as possible after an incident using best practice methods. The present research systematically tested the efficacy of a novel Self‐Administered Witness Interview Tool (SAW‐IT), an adapted version of the Self‐Administered Interview designed to elicit comprehensive information from witnesses to industrial events. The present study also examined the effect of schematic processing on witness recall. Results indicate that the SAW‐IT elicited significantly more correct details, as well as more precise information than a traditional incident report form. Contextual information about a worker's safety history biased the reports of participant witnesses, confirming that witnesses should be shielded from extraneous post‐event information prior to reporting. Importantly, these results demonstrate that the SAW‐IT can enhance the quality of witness reports.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.083
GPT teacher head0.484
Teacher spread0.401 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2019
Admission routes2
Has abstractyes

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