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Record W2994076469

The Development of Eco-Tourism in Northeast China

2015· article· en· W2994076469 on OpenAlexvenueno aff
Xiaochun Sun, Xiaolong Yang

Bibliographic record

VenueStudies in sociology of science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismChinaSWOT analysisSustainable developmentBusinessOrder (exchange)PoliticsEcotourismEnvironmental planningEnvironmental resource managementEconomic growthPolitical scienceGeographyMarketingEconomics
DOInot available

Abstract

fetched live from OpenAlex

There are rich nature eco-tourism resources, which provides reliable material foundation for the eco-tourism. Eco-tourism resources is of great significance on promoting the economic development in Northeast China. Based on the present situation of the eco-tourism resources in Northeast China, SWOT analysis is applied to analyse the advantages of current resources, region and development in Northeast China, the disadvantages of the lack of depth, protection consciousness, propaganda and cooperative efforts as well as the lag of the basic infrastructure, the opportunities of great politics, marketing and those brought by the form of the transportation hub, and the threats brought by the rapid development of surrounding areas, environment with seasonality and the low-level and out-of-order development. For this result, we came up with a stability strategy and a growth strategy, providing a useful theoretical basis for the development of the eco-tourism resources in Northeast China, and promotes the sustainable development of that.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.067
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.126
GPT teacher head0.443
Teacher spread0.317 · 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 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

Citations0
Published2015
Admission routes1
Has abstractyes

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