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Record W2251276635 · doi:10.1080/11745398.2015.1037324

At home away from home: visitor accommodation and place attachment

2015· article· en· W2251276635 on OpenAlexaff
Bianca Wildish, Robin Kearns, Damian Collins

Bibliographic record

VenueAnnals of Leisure Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVisitor patternAmenityAccommodationFeelingPlace attachmentTourismIdentity (music)Sense of placePlace identitySociologySocial psychologySet (abstract data type)AdvertisingPsychologyGeographyAestheticsPolitical scienceSocial scienceBusinessUrban planning

Abstract

fetched live from OpenAlex

Second-home owners often establish deep connections with their dwellings, and the broader landscapes of which these dwellings are part. In this research, we consider whether, and to what extent, visitors to commercial tourist accommodation also experience feelings of place attachment and home. These issues were investigated via a case study approach, centred on a youth hostel located in a high-amenity coastal area of New Zealand. The hostel’s publicly available visitor books were analysed to draw out expressions of people–place relationships, as well as key demographic information. Five themes were identified in visitors’ written reflections: repeat visits; home experience; identity and feeling; escape; and social landscape. Like the second home, the hostel provided a set of experiences considered very distinct from the typically city-based primary home, centred on a sense of freedom, relaxation and proximity to nature. It was paradoxically regarded as a place to seek change as well as familiarity. We conclude that for first-time visitors home-like experiences appear to be stimulated by social encounters and the physical environment, while for returnees they are underscored by familiarity and endorsement of identity over time.

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)0.003
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 score0.180
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.238
GPT teacher head0.475
Teacher spread0.236 · 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

Citations31
Published2015
Admission routes1
Has abstractyes

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