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Record W1851481823 · doi:10.24908/pceea.v0i0.4712

Mismatch between Anthropometric Body Dimensions and Classroom Furniture in Malaysian Universities

2012· article· en· W1851481823 on OpenAlexvenueno aff
Negin Ozve Aminian, Fairuz Izzuddin Romli

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2012
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropometrySample (material)SittingMatching (statistics)Medical educationMathematics educationPopulationPsychologyPedagogySociologyMedicine

Abstract

fetched live from OpenAlex

The main objective of study is to highlight possible mismatch between the student’s body dimensionsand the dimensions of classroom furniture used in most Malaysian universities. This issue is pertinent due to the notable increase in the number of international students who are enrolled in Malaysian universities each year. The matching of body dimensions and classroom furniture is vital to promote proper sitting posture. Body dimensions of the people from the few different countries that are perceived to make up the current student’s population in Malaysia are measured against dimensions of prevalent chairs and desks used in the classroom. The sample case study is done in Faculty of Engineering, Universiti Putra Malaysia but it is believed that the derived conclusion can also be extended to other universities in Malaysia. All in all, several mismatches have been found and highlighted for a better planning and design of classroom furniture.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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