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Gender and Tourism in the (Very) Long Nineteenth Century

2022· book-chapter· en· W4290928936 on OpenAlexaff
Cecilia Morgan

Bibliographic record

VenueOxford University Press eBooks · 2022
Typebook-chapter
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTourismScholarshipFeminization (sociology)HospitalityIndigenousGender studiesTravel writingHistorySociologyPolitical scienceLiteratureArtLawArchaeology

Abstract

fetched live from OpenAlex

Abstract The intersections of gender, travel, and tourism have received much scholarly attention, particularly since the publication of Sara Mills’s Discourses of Differences and Mary Louise Pratt’s Imperial Eyes. The travel writings and tourist experiences of European and Anglo-American middle-class women have been prominent in the field. Although much attention has been paid to their imbrication in both class and imperial relations, the wide range of women’s travel writing, its multiple layers, and the varied locations from which it was written suggest that no one model of “feminization” can be applied to its analysis. Scholars also have pointed to the gendered nature of work at tourist sites, whether in the provision of hospitality, the creation of souvenirs, and the presence of female guides. The travels of Indigenous and racialized women also help complicate our understanding of nineteenth and early twentieth-century tourist “gazes.” Although less has been written about male tourists that deploys gender as a category of historical analysis, the existing scholarship that does so suggests possibilities for future work.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.027
GPT teacher head0.181
Teacher spread0.154 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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