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Proceso metodológico y construcción de un sistema categorial de una investigación sobre identidad organizacional

2018· article· es· W2900627731 on OpenAlexaff
Diego René Gonzales–Miranda, Beatriz Amparo Uribe Correa

Bibliographic record

VenuePsicoperspectivas Individuo y Sociedad · 2018
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicOrganizational Management and Innovation
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

En este documento se expone el proceso de construcción del modelo metodológico y de los sistemas categoriales relacionados con una investigación sobre la identidad organizacional de los mandos medios desde la perspectiva de los Estudios Organizacionales. Se describe el contexto de desarrollo del trabajo y, a la vez, se explica el estudio de caso específico que enmarca el análisis de los datos y los resultados. Se examina el marco teórico, fundamento del modelo metodológico del análisis pertinente. Se señalan los pasos transitados para construir las categorías de análisis y los sistemas de categorías que permiten darle sentido a los datos obtenidos para responder a los objetivos propuestos. Se trata del proceso metodológico que subyace a toda investigación y que pocas veces se hace explícito, lo que permitirá a otros investigadores tener un referente y alternativas para la realización de su propio proyecto de construcción de sentido, un aspecto primordial -sino el más importante- del proceso de aprendizaje de todo investigador.

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)0.010
metaresearch head score (Gemma)0.013
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 score0.013
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0030.011
Scholarly communication0.0120.012
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.013
GPT teacher head0.249
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 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

Citations4
Published2018
Admission routes1
Has abstractyes

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