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Record W2140152660 · doi:10.1177/1071181312561243

Observed postural variations across computer workers during a day of sedentary computer work

2012· article· en· W2140152660 on OpenAlexafffund
Nancy L. Black, Leon DesRoches, Isabelle Arsenault

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2012
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of CanadaResearch and Innovation FoundationNew Brunswick Innovation Foundation
KeywordsWorkstationPhysical medicine and rehabilitationPhysical therapyWork (physics)Computer usersMedicinePsychologyComputer scienceMultimediaEngineering

Abstract

fetched live from OpenAlex

Sedentary computer work is widespread and typically occurs at a fixed-height seated workstation. Both neutral and at-risk postural classes of the back and neck were observed among 11computer-intensive workers using such workstations who had reported high discomfort levels. Four video recordings of approximately 1 hour each over the working day were analyzed to determine the percent duration and number of observations of each body and neck posture. Risky slouching (32.3% ±17.3%) and neck forward postures (16.9% ±12.3%) varied significantly by participant but not by time of day. Absence from video field of view of the workstation was not negligible, occurring 23.8%±14.8%. Postural changes of slouch and neck forward occurred several times during each recording (4.8±1.9 and 2.5±0.9, respectively) and varied significantly by participant but not over the day. Despite these postural adjustments, the prevalence of risky postures suggests that static workstations are fundamentally problematic.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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 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

Citations5
Published2012
Admission routes2
Has abstractyes

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Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicErgonomics and Musculoskeletal DisordersFrench-language works237,207