Dynamics of the behavior of competitiveness factors in the textile sector
Why this work is in the frame
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Bibliographic record
Abstract
The research studied the dynamics of the factors that determine competitiveness in the textile sector in Huancayo, Peru, given that in recent years it has been affected, with repercussions on profits, economic-financial stability, jobs, among others. Competitiveness is given by the interaction of various resources, actors and circumstances, which generate situations that could be auspicious or detrimental to the sector and other sectors. As a general perspective, Porter's Competitive Diamond Model and Action-Participatory Research have been used, combining scientific rigor with industrial practice. In applied research of non-experimental transactional design, an Attitude Scale was used as an instrument with 62 items and Likert-type answers, considering 7 latent variables. The methodological intervention was carried out on a sample of 75 sectoral experts. The factors that mainly determine the competitiveness of the textile sector are the structure, rivalry and strategy developed by the companies with a path coefficient of 0.812, the understanding of the behavior of the demand with a path value of 0.912 and the actions of the Government with an inverse relation of 0.824 for the respective path coefficient; while no relation has been established with the variable Integration or cluster.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it