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Record W2536121751 · doi:10.1504/ijam.2016.079953

A strategy for alleviating aviation shortages through the recruitment of women

2016· article· en· W2536121751 on OpenAlexaboutno aff
Rose Opengart, David Ison

Bibliographic record

VenueInternational Journal of Aviation Management · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachFlexibility (engineering)NationalityQualitative researchAviationEconomic shortagePsychologyPublic relationsPolitical scienceManagementEngineeringSociologyImmigration

Abstract

fetched live from OpenAlex

This mixed-methods study investigated the experiences of female pilots. Commercial and corporate female pilots answered the following question, 'How can we recruit and retain more women pilots'? 61 surveys and 10 interviews were completed by people of different gender, age, and nationality. Two qualitative software packages were utilised for analysis. The results of this study indicate that US and Canadian female pilots face significant barriers to their career paths, confirming studies in the UK and Australia. Themes found include: need for supportive other, need for confident, strong personality, parental and familial encouragement, desire for challenge and excitement, need for awareness and role models, and systems-level problems. Conclusions and implications include: remove barriers and impediments, lower cost for entry and increase initial salaries, increase visibility and outreach, address retention in addition to recruitment, leadership and organisational support, importance of culture and support, and provide more flexibility in scheduling and structure.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.127
GPT teacher head0.326
Teacher spread0.199 · 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 designTheoretical or conceptual
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

Citations19
Published2016
Admission routes1
Has abstractyes

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