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Record W2802191329 · doi:10.1002/acp.3415

Multitasking in the military: Cognitive consequences and potential solutions

2018· article· en· W2802191329 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueApplied Cognitive Psychology · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsUniversité LavalRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of CanadaDeutsches Zentrum für Luft- und Raumfahrt
KeywordsHuman multitaskingContext (archaeology)CognitionWorkloadPsychologyCognitive resource theoryResource (disambiguation)Cognitive psychologyComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

Summary Multitasking—the performance of several tasks at the same time—is becoming increasingly prevalent in workplaces. Multitasking is known to disrupt performance, particularly in complex and dynamic situations, which is exactly what most military occupations entail. Because military errors can be consequential, the detrimental impact of multitasking on cognitive functioning in such contexts should be taken seriously. This review pertains to high‐consequence military occupations that require strong multitasking skills. More specifically, it highlights cognitive challenges arising from different forms of multitasking and discusses their underlying cognitive processes. Because such challenges are not expected to diminish, this review proposes context‐relevant solutions to decrease occupational workload, either by reducing the cognitive load ensuing from the to‐be‐performed tasks or by improving soldiers' multitasking abilities. To ensure effective implementation of these solutions, we stress the need to design context‐adapted tools and procedures, and to guide human resource managers in developing particular strategies.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.274
GPT teacher head0.471
Teacher spread0.197 · 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