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Record W4220700101 · doi:10.5026/jgeography.131.23

Mechanisms for Sustaining the Local Labor Markets in International Mountain Resorts: A Case Study of Whistler, Canada

2022· article· en· W4220700101 on OpenAlexaboutno aff
Jo Komuro

Bibliographic record

VenueJournal of Geography (Chigaku Zasshi) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceRecreationWork (physics)Promotion (chess)Labor demandLabour economicsLabor relationsSettlement (finance)BusinessDestinationsTourismSupply and demandEconomicsWageGeographyDemographic economicsPolitical scienceFinanceEngineering

Abstract

fetched live from OpenAlex

This study aims to elucidate the mechanisms for sustaining local labor markets in international mountain resorts according to their regional characteristics, focusing on foreign labor. It remains unclear how international mountain resorts, which have recently struggled to secure labor to accommodate a growing number of visiting tourists, have successfully attracted outside labor to sustain local labor markets. In this case study, Whistler is an example of a resort with an imbalance between the supply and demand of labor due to an increase in demand. When analyzing labor market results in this region, a mechanism emerges that includes two processes for supplying external labor. First, the process involving those who are willing to improve their language or professional skills and obtain permanent residence rights through work promotion, changing work, or starting businesses to establish themselves in a community. Second, the process of seasonal workers going abroad with working holiday visas and for recreational purposes. A specific social regulation effect overcomes three mismatches (space, temporal, and skills) and sustains these local labor markets. In other words, the international labor force travels abroad from one market to another when the spatial divergence is resolved. The process of permanent settlement or seasonal stay of workers is enabled by addressing the divergence between temporal elements and skills in these local labor markets.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.271
Teacher spread0.262 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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