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Record W2765935025 · doi:10.1080/09640568.2017.1382337

Attitudes towards nature, wilderness and protected areas: a way to sustainable stewardship in the South-Western Carpathians

2017· article· en· W2765935025 on OpenAlexaboutno aff
Nicole Bauer, Monica Vasile, Mondini Maria

Bibliographic record

VenueJournal of Environmental Planning and Management · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
FundersDirektion für Entwicklung und Zusammenarbeit
KeywordsWildernessWilderness areaStewardship (theology)GeographyFeelingProtected areaEnvironmental stewardshipPopulationSustainable developmentQuarter (Canadian coin)Environmental resource managementEnvironmental protectionEnvironmental planningSocioeconomicsEcologyPolitical sciencePsychologySociologySocial psychologyPoliticsArchaeologyDemographyEnvironmental scienceLaw

Abstract

fetched live from OpenAlex

The acceptance and support by those who live in and around the largest remaining wilderness of Europe is very important for the success of a planned network of designated wilderness areas that should preserve the area's wilderness values. A standardised questionnaire was administered in person to 322 local residents. A cluster analysis revealed two human–nature relationship types: traditional nature users and progressive nature friends, which differ significantly in their feelings towards wilderness and attitude towards protected areas. The generally positive attitudes towards wilderness and the neutral attitudes towards the existing protected areas are a good starting point for communication about, and establishment of, the wilderness areas. As a quarter of the local population is not aware that they are living in a protected area, they should be informed during information events in the localities about the exact location of the planned wilderness zones and the potential consequences for them.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.267
Teacher spread0.251 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations25
Published2017
Admission routes1
Has abstractyes

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