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Record W2102357636 · doi:10.5267/j.msl.2011.06.003

Investigation of the effect of selected aerobic programs on improving vocational relationships

2011· article· en· W2102357636 on OpenAlexvenueno aff
Mohammad Reza Iravani, Iman Nazerian, Akram Soltani

Bibliographic record

VenueManagement Science Letters · 2011
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVocational educationComputer scienceBusinessProcess managementPsychologyPedagogy

Abstract

fetched live from OpenAlex

The new millennium has commenced with an increase awareness of precious value of human resources. Many large firms have increased to use new human resources mobilization policies and the importance of human potential in business has developed, dramatically. There different methods to help human resources increase their potentials such as providing recreational centers, athletic facilities, etc. In this paper, we study the impact of providing exercise facilities on improving the efficiency of employees in management level in the biggest steel producers in Iran called Mobarakeh Steel Complex. In this company, there were about 85 middle level managers and supervisors and the proposed study selects 30 people, randomly and divides them into two equal groups. In the first stage of the study, questionnaire of vocational relation are distributed among the participants of our experiment and we measure some important factors, which could improve vocational relationships. Next, the experimental groups are invited to take part in some selective aerobic programs for 8 weeks and 3 sessions per week and 1 hour and 15 minutes per session, regularly. Finally, we repeat the same experiments after the aerobic programs end and compare the results with the first one. The preliminary results indicate that there is a meaningful difference between the healthcares of these two groups.

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)0.001
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 score0.028
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.041
GPT teacher head0.277
Teacher spread0.236 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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