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Record W2164265109 · doi:10.5267/j.msl.2013.10.013

Application of multilevel analysis approach in management theory

2013· article· en· W2164265109 on OpenAlexvenueno aff
S. Morteza Ghayour, Shamsodin Nazemi, Fariborz Rahimnia, Mohammad Lagzian

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMultilevel modelPsychologyProcess managementKnowledge managementBusinessMachine learning

Abstract

fetched live from OpenAlex

Any phenomenon can be considered and analyzed in terms of different perspectives.In multilevel theorists view, structure or structures of the studied phenomenon are used to consider or to analyze it, completely.Level of analysis indicates the purpose of a researcher or theorist that is intended to be explained or justified, like individual, group or organizational levels and then they are generalized.Contrary to multilevel approach, the conventional approach of theorizing considers micro level or macro level.It cannot perform a simultaneous micro-macro level analysis.A multilevel approach characterized by inter-level and multilevel organizational view to organizational phenomena is an attempt to expand the boundaries of knowledge and provide a new plan.This study uses documentary studies to analyze the multi-level approach of theorizing, multilevel models and multilevel analysis.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.006
Science and technology studies0.0030.003
Scholarly communication0.0050.004
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.008
GPT teacher head0.200
Teacher spread0.191 · 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 designTheoretical or conceptual
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

Citations4
Published2013
Admission routes1
Has abstractyes

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