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Record W2105759252 · doi:10.19030/jber.v5i9.2584

Modeling The Performance Evaluation Of Local Investment And Economic Development Corporations

2011· article· en· W2105759252 on OpenAlexafffundabout
Frederic Bernard, Jean Desrochers, Denis Martel, Jacques Préfontaine

Bibliographic record

VenueJournal of Business & Economics Research (JBER) · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsDesjardinsUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsBusinessVenture capitalCorporationInvestment (military)Locale (computer software)FinanceProcess managementComputer science

Abstract

fetched live from OpenAlex

The purpose of this research is to propose an overall performance evaluation model for local development companies that takes into account social, financial and operational aspects. While there are many ways to evaluate business performance, few make it possible to take into account all the objectives of the organization. After reviewing the literature on the topic, we developed a model that uses a surface measurement to classify organizations. We then applied this model to the Société locale d’investissement et de développement d’emploi du Québec (SOLIDEQ), which itself comprises 84 SOLIDEs. The mission of these organizations is to provide venture capital to regional companies. As an arm of a labor-sponsored venture capital corporation, the SOLIDEs must obtain a return on investment commensurate with the risk incurred, achieve local development objectives such as job creation and maintenance, and lastly, manage operations wisely given that the management committee consists of volunteers. The study results show that our model can be effectively used to measure the performance of each SOLIDE and to create a classification that takes into account all their objectives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.146
GPT teacher head0.288
Teacher spread0.142 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2011
Admission routes3
Has abstractyes

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