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Record W2889878786

Contributos do lazer desportivo outdoor na criação de novos campos de pensar e agir

2016· article· pt· W2889878786 on OpenAlexvenueno aff
Alcides Vieira Costa, Maria Altina Almeida, Carlos Colaço, Alberto Reinaldo Reppold Filho

Bibliographic record

VenueService social · 2016
Typearticle
Languagept
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Environmental educationExploratory researchSustainable developmentSociologyHumanitiesGeographyPolitical sciencePedagogySocial science
DOInot available

Abstract

fetched live from OpenAlex

The development of outdoor activities is a topic that has been discussed by many sectors of society over the years. These activities can be important catalysts for the social development and recovery of regions weakened from the social, economic, demographic and environmental point of view. This study aims to establish the contributions brought by outdoor activities to the creation of new ways of thinking and acting, based on the analysis of social and economic benefits, for practitioners and for the environment. The research was an exploratory study in a qualitative approach that analyzed information from interviews, documents and observations. The documents consisted of guidelines, programs and plans on the geographical and socio-environmental characteristics of the practice sites in the city of Porto Alegre, Brazil. The interviews, in a total of 29, were held with representatives of government, sports federations, NGOs, lecturers of higher education institutions, entrepreneurs and outdoor activities instructors. The observations, 8 altogether, occurred in regions with geographical features that allow the practice of such activities. The results showed that the contributions of outdoor activities are important catalysts for new thinking and acting perspectives, having a social, economic and environmental positive impact in the regions where these activities are developed in a sustainable way.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.031
GPT teacher head0.330
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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