The folk as a resource in the construction of the tourism image of Alto Minho (Portugal)
Bibliographic record
Abstract
"Based on the analysis of the discourse (s) on Portuguese folklore and the rescue of the past and the traditions through the invention/ reinvention of the cultural heritage, the objectives of the research are focused on the study and the valorization of folklore while An an important resource that shapes the image of Minho (Northern Portugal). We also propose to identify some of the most representative folk groups and to analyze the repercussions of the use of these manifestations of popular culture, especially the traditional dances and songs of the Alto Minho region (Portugal), in the formulation of the image of the destination, with special incidence in the district of Viana Of the Castle Viana do Castelo. We also propose to ascertain to what extent these folkloric manifestations have broadened their function of affirming the cultural identity of the receiving community. And how can we discuss an eventual deconstruction of the identity brought about by tourism? Taking into account the epistemological framework of the Social Sciences, we propose to adopt fundamentally the qualitative/ deductive methodologies since we will start from a documentary collection and analysis of the folklorist discourse (s), plus the unstructured and open data collection, namely open interviews and observation participant. The research design follows an ethnographic matrix with the use of deductive methodologies, and the guiding thread of the narrative presents a duality of the way folklore is conceived, an analysis that focuses on the confrontation and overlap of the so‑called “paradigm of recomposition” Which formulates it as a representation of past customs and tradition and the pattern of ‘stylization’ which expresses folklore as an ‘object’ in itself."
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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 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".