MétaCan
Menu
Back to cohort
Record W7075668768

The spectacular traveling woman: Australian and Canadian visions of Women, Modernity, and Mobility between the Wars

2019· article· en· W7075668768 on OpenAlexaboutno aff

Bibliographic record

VenueArrow@dit (Dublin Institute of Technology) · 2019
Typearticle
Languageen
FieldComputer Science
TopicData Analysis with R
Canadian institutionsnot available
Fundersnot available
KeywordsVisionScholarshipInterwar periodGirlLaunchedIntersection (aeronautics)
DOInot available

Abstract

fetched live from OpenAlex

This article applies recent scholarship concerned with transatlantic mobility and print cultures to a comparative study of images of trans-Pacific travel for women during the interwar period. During the 1920s and 30s female travelers splashed spectacularly across the pages of mainstream, popular magazines, produced in America, Britain and the wider Anglophone world. Focusing on two magazines that launched in this era, The Australian Woman’s Mirror (1924-61) and Chatelaine (1928-), this article explores Australian and Canadian fictional portrayals of the traveling woman of the interwar years to examine the ways in which the mobility of the modern girl became a screen for anxieties and fantasies of these two national print imaginaries. By paying attention to the different portrayals of female mobility through the Pacific from both sides of the ocean, this article also considers the intersection between actual travel, ideas about travel, and notions of gendered social mobility.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.073
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0170.011
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.238
Teacher spread0.226 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueArrow@dit (Dublin Institute of Technology)Same topicData Analysis with RFrench-language works237,207