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Record W2008870752 · doi:10.5539/ies.v3n2p219

On Application of MBO in College Management

2010· article· en· W2008870752 on OpenAlexvenueno aff
Xihuai Liu

Bibliographic record

VenueInternational Education Studies · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsnot available
Fundersnot available
KeywordsManagement by objectivesDemocracyWork (physics)ManagementBusinessProcess managementSociologyPolitical scienceEngineeringEconomicsPolitics

Abstract

fetched live from OpenAlex

MBO (Management by objectives) was firstly put forward by peter F. Drucker (who was a well-known scholar of management in America) in 1954 .MBO was applied in many organizations after a number of management scholars developed and perfected it . MBO is a comprehensive and democratic systemic management style which is work-centered and people-centered. At first, MBO was widely applied in management of enterprise as a kind of democratic management fashion. This paper organically make some characteristics of MBO and college management together to talk about the feasibility and importance of MBO in college management, as well as several questions should be noticed and tasks of leaders about MBO in college management.

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.008
Scholarly communication0.0050.007
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.329
Teacher spread0.313 · 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 designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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