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The School of Posture as a Postural Training Method for Paraíba Telecommunications Operators

2001· article· en· W2056964716 on OpenAlexaboutno aff
Maria Cláudia Gatto Cárdia, Francisco Soares Másculo

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2001
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety in Workplaces
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Sample (material)Work (physics)PopulationQuality (philosophy)Point (geometry)Physical therapyApplied psychologyPsychologyEngineeringOperations managementTelecommunicationsMedicineEnvironmental healthMathematicsGeography

Abstract

fetched live from OpenAlex

This work proposes to show the experience of posture training accomplished in the Paraíba State Telecommunication Company, using the knowledge of the Back School. The sample was composed of 12 operators, employees of the company, representing 31% of this population. The model applied in TELPA (Paraíba Telecommunication Company, Brazil) was based on the models of Sherbrooke, Canada, and of the School of Posture of Paraìba Federal University. Fifty-eight point four percent of participants showed a reduction of column pain, 25% improved the quality of the rest and the received training was considered enough for the learning of correct postures at work in 75% of the cases. The whole population approved of the training, and 83.3% of the cases considered that this training influenced their lives very positively.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.071
GPT teacher head0.473
Teacher spread0.402 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2001
Admission routes1
Has abstractyes

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