The Effects of Innovative Features of Women Managers on their Business Performance: The Food Exporter Companies in Aegean Region Sample
Bibliographic record
Abstract
The main aim of this research is to determine perceptions of innovative features of women managers in food exporter companies in Aegean Region on their business performance. The questionnaire prepared on this subject and on January 2015–March 2015 was applied to the 123 women managers working in food exporter companies in Aegean Region. At the end of the research in the 20 scope proposition collected in the eight factors; it was determined that within the framework of innovative features, women managers ownership of the mission and vision, care about career development (f1), to see opportunities, to be brave, to be open to learning (f2), to be conciliatory and to be convincing (f3), to be prescience and to be creative (f4), to be solution-oriented and to be open to innovation (f5), to care about cooperation, research and high communication (f6), to be emotional and abstract thinking (f7), high confidence and to be competitive (f8), affected business performances of them in the advanced positive way. For the 20 propositions, the alpha value of Cronbach is 0,726. Eight factors overall variance is explained at %79,174 levels.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".