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Record W4400002990 · doi:10.1080/09669582.2024.2371498

Gender equality in a Chinese rural tourism destination: perspectives of females and males

2024· article· en· W4400002990 on OpenAlexaff
Ming Su, Menghan Wang, Geoffrey Wall, Zhenhua Liu, Hangyu Dong, Mengzhen Zhang

Bibliographic record

VenueJournal of Sustainable Tourism · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTourismRural tourismGender equalityGeographyGender relationsDestinationsGender studiesSociologySocioeconomicsTourism geography

Abstract

fetched live from OpenAlex

Gender equality is an important UN sustainable development goal. With tourism often encouraging and favoring female participation, relationships between tourism and gender equality have attracted much research attention. However, being dynamic and highly contextual, the multi-faceted complex of gender and tourism interactions are relevant to both males and females. Therefore, nuanced and contextual case studies incorporating perspectives of both genders is critically needed for gender research in tourism. Drawing from previous research, dimensions of gender equality are deconstructed into gender roles, perspectives, and relationships. Yudong Village, Zhejiang Province, China, was selected as the study site. Field investigations were used, primarily involving semi-structured interviews with multiple actors. Females and males were interviewed to acquire and compare their involvements in and perspectives on tourism and its influences on gender issues. Positive tourism influences on three dimensions of gender equality were acknowledged by both genders. Relationships among changes in gender perceptions, roles and relationships were examined. Agreements and differences between genders and across generations are discussed. Such changes rippled from family circles to rural communities through tourism enhanced social networks and business relationships. This research contributes to a gender balanced understanding of tourism impacts on gender equality. Practical implications are discussed.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.364
Teacher spread0.332 · 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

Citations13
Published2024
Admission routes1
Has abstractyes

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