Challenges to Undertake and Innovate in Colombia: Is the New Problematic of the 21st Century?
Bibliographic record
Abstract
Entrepreneurship in general brings with it certain challenges and risks, which generate a long learning path before reaching success; Colombia for example, there is a complex panorama, the entrepreneurs are limited, and the entrepreneurship projects are not executed with totality. Therefore, the article´ objective is to identify the main factors that impede the work of undertaking in Colombia; supported by sources of descriptive information from previous studies focused on the transition from academia to industry, which were elaborated by recent students and graduates students in Colombia. The above, allowed to synthesize that the main obstacles of entrepreneurship are framed in collective and cultural thinking, or academic training in the face of entrepreneurship where a bureaucracy, tramitology and innovation end with the visible need to restructure sociocultural and business models, generating an efficient and constant transition that leads to the economic development of the country increasing, in turn, the quality of life of society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".