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Record W2164812711 · doi:10.5267/j.msl.2013.05.013

An application of AHP method for ranking administrative headquarters of the state welfare in Iran

2013· article· en· W2164812711 on OpenAlexvenueno aff
Mohammad Hakkak

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsnot available
Fundersnot available
KeywordsAnalytic hierarchy processRanking (information retrieval)WelfareState (computer science)Computer scienceOperations researchBusinessOperations managementArtificial intelligencePolitical scienceEngineeringLawAlgorithm

Abstract

fetched live from OpenAlex

The purpose of the present study is to prioritized different methods for making necessary change on the administrative system of the central state Welfare Organization in Iran.The proposed model of this paper uses descriptive and measuring approach based on 11 questionnaires, which include criteria and necessary options to change the administrative system.The proposed model selects the sample size from different management levels, human capital development assistance, top, middle, and operational mangers of central state Welfare organization.Analytical hierarchy process (AHP) technique is used to perform pairwise comparisons and Expert Choice is implemented to analyze the information.The results indicate that structure and process correction are the primary requirements for systematic changing.Weight of mentioned index is 0. 203 and the Compatibility Rating of changing criterion is equal to 0.06.

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)0.008
metaresearch head score (Gemma)0.011
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: Methods · Consensus signal: Methods
Teacher disagreement score0.015
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.114
GPT teacher head0.449
Teacher spread0.334 · 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
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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