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Record W1830027626 · doi:10.5200/321

The Working Environment and Health Of Specialists Working with Computers

2012· article· en· W1830027626 on OpenAlexaboutno aff
Sigitas Griškonis, Birutė Strukčinskienė, Juozas Raistenskis, Ieva Griškonytė

Bibliographic record

VenueSveikatos mokslai / Health Sciences · 2012
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsWorking environmentWorking timeWork (physics)Working hoursWorking ageQuarter (Canadian coin)Table (database)MedicinePsychologyEngineeringComputer scienceEnvironmental healthDatabasePopulationGeography

Abstract

fetched live from OpenAlex

The survey on working environment and health of specialists working with computers was accomplished in Lithuania in 2011. In the survey participated 204 specialists working with computers at the offices, at small and medium sized business companies. Chi-square test was used and the significance level p ≤0.05 was considered statistically significant. The study revealed as about one-third (33 %) respondents work with computer all working day, 26% work 4 hours, and 24% work 6 hours per day. Men and women work with computer similar number of hours per day.Most of specialists working with computers (60%) use modern computer chair with modifying elements. Almost one-third (29%) respondents think that their chair is uncomfortable. 24% respondents use the working table with unsuitable high, 31% use the working table with too small area and insufficient space. Only quarter (25%) specialists working with computers work at very good illumination, and 55% - at good illumination. Significantly more men than women use modern computer chair (p=0.035). The computer equipment at men‘s table are located more convenient than at women‘s (p=0.046). Nearly half (43%) workers with computers are disturbed at work by strangers, and 18% - by noise. To concentrate and work for men disturb noise, and for women disturb noise and strangers. Physical discomfort could be reduced by using working chair with castors, working chair with the ability to change the heigth of the chair, and the chair with elbow-rests. Article in Lithuanian doi:10.5200/sm-hs.2012.076

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)0.002
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 score0.440
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.065
GPT teacher head0.332
Teacher spread0.268 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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