MétaCan
Menu
Back to cohort
Record W2019145596 · doi:10.1080/15022250.2014.999015

Looking for Experience at Vittangi Moose Park in Swedish Lapland

2015· article· en· W2019145596 on OpenAlexaff
Consuelo Griggio

Bibliographic record

VenueScandinavian Journal of Hospitality and Tourism · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVisitor patternTourismFeelingSet (abstract data type)AestheticsSociologyNational parkDatabase transactionEvent (particle physics)PsychologyEnvironmental ethicsGeographySocial psychologyArtComputer scienceArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

The study aims to enrich our knowledge of the nature and practices beyond the experience of the encounter between visitors and wild animals in a tourist setting such as a moose park. Drawing upon Walter Benjamin's distinction, the paper argues that the experience at Vittangi Moose Park is an Erfahrung, that is, a set of knowledge that becomes meaningful through its shared nature. The experience is created through a bodily and visual transaction between visitors and moose. Through touching, feeling, and feeding the moose, visitors wish to understand the animal and aim to establish a dialogue with it. By taking pictures and sharing them with friends and family at home, visitors not only consume places, landscapes, and experiences but also produce and reproduce them. The bodily and visual experiences thus come to represent a totalizing multi-sensual event in which the visitor experiences the animals actively, expressively, reflectively, and imaginatively.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueScandinavian Journal of Hospitality and TourismSame topicGeographies of human-animal interactionsFrench-language works237,207