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Record W2900771395 · doi:10.1080/17449359.2018.1547647

Amodern and modern warfare in the making of a commercial airline

2018· article· en· W2900771395 on OpenAlexafffund
Nicholous M. Deal, Albert J. Mills, Jean Helms Mills

Bibliographic record

VenueManagement & Organizational History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsSaint Mary's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeExtant taxonPower (physics)SociologyReading (process)Military historyModern warfareStyle (visual arts)SalientOrganization studiesKey (lock)HistoryLawPolitical sciencePsychologyComputer securityLiteratureComputer scienceSocial psychologyArchaeologyArt

Abstract

fetched live from OpenAlex

This paper focuses on the impact of warfare, gender, and memory on the development of Imperial Airways (British Airways’ predecessor airline). Through a ‘close reading’ of archival materials and published histories, we examine how wartime experience prior, during, and following World War I came to shape the development of gendered organizational processes and practices in the airline’s emergent organizational culture from 1924–1939. Gender is theorized from a feminist poststructuralist position serving to problematize singular notions of power. Analysis of culture is explored through an ANTi-History and microhistorical approach revealing how history is produced and constitutes the ‘sense’ of organization. We examine how references to warfare are introduced into the narratives of Imperial Airways and its predecessor airlines, how warfare is utilized in the airline’s historical accounts, and how this influences our understanding of gender over time. Findings suggest two key aspects of memory at play. Memory of warfare is more embedded in cultural practices (e.g. piloting as male only) and symbolism (e.g. military-style pilots’ uniforms) than in extant narratives of the time. However, despite the Women’s Royal Air Force in 1918 and exploits of pre-war female flyers, women’s role in warfare was largely forgotten at all levels of the airline.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.016
Scholarly communication0.0060.006
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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
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

Citations23
Published2018
Admission routes2
Has abstractyes

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