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Record W1990840453 · doi:10.1080/1068316x.2011.599325

Of guns and geese: a meta-analytic review of the ‘weapon focus’ literature

2011· review· en· W1990840453 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

VenuePsychology Crime and Law · 2011
Typereview
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsMacEwan UniversityLakehead UniversityDalhousie University
Fundersnot available
KeywordsPsychologyScholarshipSchema (genetic algorithms)Social psychologyEvent (particle physics)Applied psychologyComputer scienceLawPolitical science

Abstract

fetched live from OpenAlex

Abstract Weapon focus is frequently cited as a factor in eyewitness testimony, and is broadly defined as a weapon-related decrease in performance on subsequent tests of memory for those elements of an event or visual scene concurrent to the weapon. This effect has been attributed to either (a) physiological or emotional arousal that narrows the attentional beam (arousal/threat hypothesis), or (b) the cognitive demands inherent in processing an unusual object (e.g. weapon) that is incongruent with the schema representing the visual scene (unusual item hypothesis). Meta-analytical techniques were applied to test these theories as well as to evaluate the prospect of weapon focus in real-world criminal investigations. Our findings indicated an effect of weapon presence overall (g= 0.53) that was significantly influenced by retention interval, exposure duration, and threat but unaffected by whether the event occurred in a laboratory, simulation, or real-world environment. Keywords: weapon focuseyewitness memorymemoryattentioncognition Acknowledgements JMF was supported by an NSERC Canada Graduate Scholarship and a Killam Predoctoral Scholarship, and would like to thank Dr. Ray Klein for comments on an earlier draft of this manuscript. KAP would also like to thank Jessica Gilbert for her research assistance. Finally, we would like to thank Dr. Kerri Pickel, Dr. Brian Bornstein and our anonymous reviewers for their feedback.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.160
GPT teacher head0.435
Teacher spread0.275 · 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