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Record W4361197616 · doi:10.1080/09523367.2023.2189237

The Evolution of Hanne Wassermann’s ‘ <i>Gymnastik Methode</i> ’ in Vienna’s Golden Autumn

2023· article· de· W4361197616 on OpenAlexaff
Patricia Vertinsky, Aishwarya Ramachandran

Bibliographic record

VenueThe International Journal of the History of Sport · 2023
Typearticle
Languagede
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurriculumSociologyPsychologyPsychoanalysisPedagogy

Abstract

fetched live from OpenAlex

Hanne Wassermann’s contributions to teaching gymnastics and body culture during Vienna’s interwar period took place within the rich contexts of ongoing developments in radium research, psychology, physiology and anatomy, and gynecology. This paper explores the movement theories she developed for her classes as well as the ways in which she distinguished her teaching from other renowned female physical culturalists of the time. In ‘Tägliche Gymnastik’, a workbook on daily gymnastics that Hanne co-edited with Jewish gynecologist Oskar Frankl in 1934, and other published and unpublished manuscripts, she described the psychological theories supporting her ‘Gymnastik Methode’—mainly the principles of Gestalt psychology learned from psychologists Karl and Charlotte Bühler at the Vienna Institute of Psychology. She was able to tap into a remarkable network of associates and acquaintances, including celebrated physicians, scientists, movie stars, multi-millionaires, and royalty—and use their influence and status to popularize and begin to commercialize her ‘Gymnastik Methode’, as well as to assist her escape from Vienna following the Anschluß Österreichs (Annexation of Austria) and develop a successful career in massage and remedial gymnastics in North America. She took with her copies of ‘Tägliche Gymnastik’ and the as yet unpublished ‘Methode’ which became important supports to her future livelihood in North America.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.048
GPT teacher head0.286
Teacher spread0.237 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of the History of SportSame topicMedical History and ResearchFrench-language works237,207