CULTURA DE LAS PROFESIONES EN LA EMPRESA ASTILLEROS DEL ORIENTE. CONSIDERACIONES TEÓRICO METODOLÓGICAS
Bibliographic record
Abstract
The complexities of the Cuban context need solutions that articulate realities, strategies, and political and scientific perspectives; however, despite the diversity of disciplines, approaches, studies, and authors that approach the organizational culture and the theory of professions, the use of the concept: culture of professions, is barely noticeable in national and foreign research on organizational cohorts, at a time when this category needs to acquire more significant value. This work aimed to characterize the culture of professions in the Astilleros del Oriente (ASTOR) Company to identify theoretical-methodological guidelines for its use in the workplace. This investigation was carried out as a case study in the dependences of ASTOR, in Santiago de Cuba, with a population of 296 people of different professions; it was necessary to harmonize methods and technical qualitative and quantitative as interviews, surveys, observations, and analysis of documents, being applied a simple random sampling in the case of the survey and intentional samplings for the other instruments. The main result was the theoretical-methodological construction of the concept culture of professions and the identification of rules for its use in the labor sphere employing the characterization of the organization study object.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".