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Record W1480683779

NTOs and State Policy: The Paradigms of Political Economy and Insitutional Response to Tourism in Times of Economic Crisis

2009· article· en· W1480683779 on OpenAlexaboutno aff
Craig Webster, Stanislav Ivanov, Steven F. Illum

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsMercantilismPoliticsState (computer science)TourismPolitical economyPolitical scienceDemocracyFinancial crisisEconomic systemDevelopment economicsEconomicsEconomyKeynesian economicsLaw
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we look at the three broad capitalist models for political/economic organization upon which states organize themselves and then explore examples of those states and each country’s response to tourism. In order to investigate this, we take two examples of social democratic states (Sweden and Finland), two examples of liberal states (the USA and Canada), and two examples of mercantilist states (South Korea and Japan) to see how the state organizes itself in terms of tourism. We find that countries with liberal, mercantilist, and social democratic political and economic systems have very different institutions to deal with tourism, with liberal states tending to have weak state institutional responses to tourism while mercantilist states have strong ones. The investigation has implications for states in the current financial crisis, since the state’s response to the crisis will either be consistent with the political philosophy upon which the state’s institutions rest or run counter to the prevailing political and economic thinking upon which the state’s institutions rest.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.021
Scholarly communication0.0080.006
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.283
Teacher spread0.271 · 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 designNot applicable
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

Citations1
Published2009
Admission routes1
Has abstractyes

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