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DIFFERENCES IN FINANCIAL PERFORMANCE AMONGST SPANISH SMES ACCORDING TO THEIR CAPITAL‐OWNERSHIP STRUCTURE: A DESCRIPTIVE ANALYSIS

2010· article· en· W1981528998 on OpenAlexaff
Zuray Melgarejo, Katrin Simón, F.J. Arcelus

Bibliographic record

VenueAnnals of Public and Cooperative Economics · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsUniversity of New BrunswickNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsBusinessDescriptive statisticsCapital (architecture)FinanceCapital structureAccountingStatisticsGeography

Abstract

fetched live from OpenAlex

ABSTRACT ** : The purpose of this paper is to assess whether financial performance differences between labour‐managed (LOFs) and mercantile (PCFs) firms are due to differences in their capital‐ownership configuration or to the particular measurement indexes commonly used to quantify performance. The empirical evidence rests upon a 1994–2003 data set of LOFs and PCFs that operate in the Industrial and Services sectors of the economy of Navarre, Spain. The results do not detect significant differences in financial performance between LOFs and PCFs, especially in the long‐term and suggest the need to develop performance indices more akin to the special nature of the LOFs.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.054
GPT teacher head0.230
Teacher spread0.176 · 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 designObservational
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

Citations10
Published2010
Admission routes1
Has abstractyes

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