Familiar Microcompany and empreendedorismo in the quarter Are Peter in Teresina-PI
Bibliographic record
Abstract
The process of globalization brings with it the competitiveness as one of the main features of market economies. Feeling that the development of entrepreneurial skills, more than ever becomes a constant need within the business. With regard to the characteristics micro entrepreneurs are proving as an important tool to gain in competitiveness, so for his stay in market. Starting from this scenario of the market as they aim of this study assess the presence of the characteristics of entrepreneurs\nin micro family neighborhood of SÃo Pedro in municipality of Teresina in state of Piaui. The study makes a brief review of theories on the family business and, its relationship with entrepreneurship, and based their analysis on the theory of behavior entrepreneur, of David McClalland (1987), as well as in literature found. The type of research is exploratory, empirical, and descriptive. The information was obtained by direct search. The universe of search was constituted by 109 micro of the neighborhood SÃo Pedro in Teresina, PiauÃ, identified by the survey conducted by us. Conclude that all the companies surveyed with more than 5 years existence, the theory of behavior enterprise of McClalland, demonstrating the validity of variables indicator of entrepreneurial behavior.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.082 | 0.009 |
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".