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The Nature of Pleasure in Pleasure Travel

2009· article· en· W2018466850 on OpenAlexaff
David A. Fennell

Bibliographic record

VenueTourism Recreation Research · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsBrock University
Fundersnot available
KeywordsPleasurePleasure principleTourismPsychologyTheme (computing)Field (mathematics)AestheticsSociologyEpistemologySocial psychologyGeographyPhilosophyComputer science

Abstract

fetched live from OpenAlex

It is indeed ironic that despite the importance of pleasure as a central theme in both the practice and theory of travel, there is a critical absence of knowledge from which to theoretically and conceptually situate this concept in our field. Given this current state, the purpose of this paper is to undertake a general survey of literature on pleasure, incorporating knowledge from a number of diverse fields including philosophy, evolutionary biology, psychology, neuroscience, social psychology, sociology, and tourism. More specifically, the paper examines sensory or qualitative forms of pleasure and these are compared and contrasted with emotional or attitudinal forms of pleasure, including satisfaction, enjoyment and aesthetics. These different types of pleasure are later organized into a conceptual framework and linked with different temporal frames of pleasure, including anticipatory, on-site, and remembered temporal contexts. This arrangement, along with the interdisciplinary nature of the work, is viewed eis a point of departure for further research in the area.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.014
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.069
GPT teacher head0.433
Teacher spread0.364 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

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