Improving workplace incident investigations by enhancing memory recall
Bibliographic record
Abstract
Abstract Purpose – Industrial incident investigations determine what caused an adverse workplace event so that preventative measures can be instituted and reduce the risk of such incidents happening again. Investigators gather evidence from multiple sources in an investigation and one such source is the people in, or around, the industrial incident. The purpose of the current study is to examine if recall strategy could affect eyewitnesses' recollections of a workplace incident. Design/methodology/approach – The current study is a 3 (Post‐Event Context: Think, Filler, Discuss)×2 (Incident Investigation Form: Psychologically‐Based vs. Standard Investigation Form) between‐subjects factorial design. Participant‐witnesses watched a simulated videotaped workplace incident (n=196) then either: thought about the event, discussed it with fellow witnesses, or engaged in an unrelated task. Subsequently, participants recalled the details of the adverse event on an incident report form: a Standard Investigation Form or a form based on principles of cognition (Psychologically‐Based Form). Findings – Compared to the Standard Investigation Form condition, eyewitnesses in the Psychologically‐Based Form condition recalled significantly more pieces of accurate information at a reduced accuracy rate. Post‐event context produced no significant differences in participant‐witnesses' reporting. Practical implications – The data suggest that incorporating some principles of memory and cognition into incident investigations have the potential to enhance accurate recollection of a workplace event. Originality/value – This study is among the first to apply psychological theory to enhance eyewitness reports of an industrial incident. In so doing this research contributes to recent literature that explores eyewitness recall for industrial events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".