Plan de marketing social para incentivar las actividades físicas - recreativas en adolescentes femeninas, cantón quevedo, año 2015”
Bibliographic record
Abstract
This research was conducted in Quevedo town, Los Rios Province, Republic of the Ecuador, during the third quarter of 2014. It was considered as a general objective to design the four basic components of the marketing mix of social marketing plan to encourage physical recreation in female adolescents, Quevedo, 2015. The investigation came mainly to the following conclusions: 62% of female adolescents surveyed said that there is no offer of sports programs in their area (neighbor or parish) and there is a little range of recreational activities at school (walking, hiking, bailoterapias, etc.). 44% believe that girls do not participate in recreational activities because no one's organized them. 28% believe the cause is lack of dissemination activities. 74% said no recreational activities are organized in her parish. 44% prefer sports fields for recreational activities. 62% prefer to directly participate in recreational activities of their parish. 25% said they prefer to practice female and 19% Indoor prefers basketball. Recreational physical activities will be organized in weekly sessions (weekend) for each urban parish of the town and will be sporting nature (female Indoor and basketball), leisure (Traditional Games. Sacks, blind man's bluff Fifty-stick, The Hidden, etc.), socialization (presentation of cultural events) and contact with nature (walking with friends / River roadTour/ swimming). Thespecifichypothesisweretestedentirely.
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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 | 0.001 | 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) | 0.005 | 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".