Bibliographic record
Abstract
It is estimated that 95 per cent of pilots in civil aviation are men and there is little progress being made in increasing numbers of women pilots globally. Gender issues such as hegemonic masculine cultures, employment discriminations and the social exclusion of women seem to have changed little since the publication of our co-edited book Absent Aviators in 2014. This chapter considers to what extent the gendering of airline history, and the gendering of women’s involvement in aviation, contributes to the problem of gender segregation in the industry. We examine three international airlines – Air Canada, British Airways and Qantas – through the lens of history texts. In doing so we apply an “intersectionality: history over time” framework to the analysis of historical texts. Following the tradition of Kerry Hendricks and colleagues, we acknowledge the “heuristic value” of intersectionality as a framework enabling the investigations into discrimination that has occurred historically and continues to occur in the present day. Charting discriminatory practice through time and across national and organisational contexts allows insight into organisational practices and national trends. This allows insight into how historical belief systems and practices create present realities for women in aviation today.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".