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Record W2135534269 · doi:10.5539/res.v7n4p234

A Process Approach to Management of an Educational Organization

2015· article· en· W2135534269 on OpenAlexvenueno aff
Elena Y. Levina, Yuliya L. Kamasheva, Фарида Самигулловна Газизова, Almira K. Garayeva, Indira Salpykova, Gulnaz F. Yusupova, Nikolai V. Kuzmin

Bibliographic record

VenueReview of European Studies · 2015
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Teacher Development
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Educational managementQuality (philosophy)Product (mathematics)Educational organizationProcess managementBusinessKnowledge managementQuality managementEngineering managementComputer scienceSociologyEngineeringPedagogyMarketingService (business)

Abstract

fetched live from OpenAlex

Directions for an educational organization development meet the requirements of society to the effectiveness and quality of educational activities in high dynamics of external and internal environment. The article examines the potential of the process approach, which considers management as a continuous performance of certain interrelated activities complex and general management functions when developing a quality management system of an educational organization. In the submitted article the components of the educational activities process are defined, which are based on the quality standard of the final product. This article is intended for educators, researchers, heads of educational institutions, employers, customers of educational services, education management organizations employees.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0040.018
Scholarly communication0.0140.011
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.162
GPT teacher head0.408
Teacher spread0.246 · 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 designQualitative
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

Citations13
Published2015
Admission routes1
Has abstractyes

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