Leadership in the face of digital transformation in an Ecuadorian manufacturing company in 2020
Bibliographic record
Abstract
The present research focused on determining the predominant leadership style in the productive areas of an Ecuadorian manufacturing company, and the level of digital transformation during the year 2020. The study was developed through cross-sectional descriptive research. The multifactorial leadership questionnaire and key performance indicators were used as instruments, which were applied digitally using Google forms. The population studied was 151 workers and the sampling technique was probabilistic. The results allowed determining that 74% of the transformational leadership guidelines are practiced, 77% of transactional leadership and 9% of laissez-faire. The level of digital transformation had an increase of 19% in the fourth quarter compared to the first quarter of the year, evidencing in practice the implementation of automation mechanisms, use of digital media and documents and implementation of technology. It was concluded throughnthe literature and theoretical review that to face the technological advance, the transformation leadership style with all its dimensions is the most appropriate because it promotes development, innovation and knowledge management
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".