THE MSMES. ANALYSIS FROM CORPORATE LAW, CUBAN REALITY
Bibliographic record
Abstract
The article carries out an analysis of the private entrepreneur and its conversion as a Limited Liability Company in Corporate Law, how it has been introduced into the Cuban legal system from its origins, characteristics as a new economic actor, elements that distinguish MSMEs , legal nature, social order conceived for the execution of commercial activities in joint trade acts with the public company, mandated from the constitutional text of 2019, in the update of the new Cuban social economic model.The methods used were the analysis, synthesis of materials from Commercial Law to break down the information, the logical history of the stages of Corporate Law of the SRL, induction deduction to deduce and arrive at elements of value judgments, the legal exegetical, the bibliographic review of materials on MSMEs, and the legal comparison of legal norms on the constitutive process of the commercial company.The analysis of the normative regulation of the MIPYMES in Cuba, as an actor in the productive development for its contribution to the generation of jobs, in the number of companies and, for its weight in the GDP of the country.Required preferential tax treatment, facilities for access to financial credit by the Bank, entities that oversee its development and promotion, that regulate the diversity of legal forms that they adopt as businesses in the legal system such as SRL, SURL or SL in attention to the Commercial Code and substantive law, and the need to issue a Business Law, which sets out the boundaries and demarcations with the public company.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".