Características del baile de la marinera en la festividad de san isidro labrador en moche y su contribución a la promoción del destino de trujillo
Bibliographic record
Abstract
This thesis aims to promote the destination Trujillo by the spontaneous and traditional dancing sailor in Moche, to publicize the importance and acceptance that this resource has its population and tourists. The dance of the fishing practiced in the feast of San Isidro Labrador comes from generation to generation and learning is by imitation and oral traditions; features that would be reason to promote the destination as a result of Trujillo and promote the destination Trujillo generate displacements towards the village of Moche. On the other hand the people of Moche fully claim the spontaneous dancing and traditional seafood can indeed promote the destination Trujillo. The moments that the spontaneous and traditional seafaring practiced are reflected in the dancing, the type of clothing that behaves, and how this event is manifested in the religious festival of San Isidro Labrador. Finally, it is important to take into account the spontaneous and traditional dancing sailor presented in religious festivities in Moche, and make this a tourist attraction with proper promotion, with the aim of which is recognized, accepted and become the main motivation for tourists. The methodology used for research, is the Ethnographic Method and Inductive-Deductive Method. The techniques used were: Direct Observation No Participant Survey and Interview. The instruments used were: Fieldbook, Guide interview, questionnaire survey, camera, camcorder and digital camera-mp3 voice recorder.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".