As intenções de viagem pós pandemia, uma análise preditiva da demanda
Bibliographic record
Abstract
A pandemia de Covid-19 trouxe diversas mudanças na vida dos brasileiros pela necessidade do isolamento social. Neste contexto, o setor de turismo no Brasil passou a vivenciar um momento crítico com a paralização total das atividades. Este estudo tem como objetivo analisar o impacto da pandemia do Covid-19 no turismo brasileiro e o comportamento planejados os dos consumidores de viagens pós pandemia. A metodologia da pesquisa trata-se de pesquisa quantitativa e descritiva, com a amostra de 391 pessoas de todas as regiões brasileiras, consumidores de serviços turísticos, os tratamentos dos dados serão apresentados por meio de análise descritiva e regressão múltipla. De acordo com os resultados da pesquisa, 62,4% dos respondentes possuem interesse em realizar viagens turísticas de acordo com o planejado anteriormente, porém, para 58,5% dos respondentes, o número de casos da Covid-19 afeta diretamente a intenção de viagens dos consumidores. Especialmente, no segmento de turismo os consumidores se apresentam bastante cuidadosos e com uma preocupação quando se trata de viagens turísticas. Diante disto, especificamente é possivel verificar o impacto causado pela pandemia para as empresas do segmento.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".