A Feminized Language of Democracy? The Representation of Women at Westminster since 1945
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 1919, Nancy Astor took her seat in the House of Commons as Britain’s first ever female MP. In the 1945 election, the number of women in the house nearly trebled to twenty-four, and remained around this level for the next four decades. In Tony Blair’s landslide victory in 1997, 120 female MPs were returned, and women have since comprised around 20 per cent of the Commons. The 2015 election saw 191 elected: the most ever. But to what extent has the increasing presence of women in Parliament made more than a symbolic difference? For example, have female MPs represented a hitherto marginalized ‘women’s interest’, placed ‘women’s issues’ on the agenda, or added a feminine perspective to existing discussion? Using 677 million words of digitized parliamentary speech, and drawing upon the outputs of the Digging into Linked Parliamentary Data (‘Dilipad’) project, we perform a wide-ranging empirical analysis of the role of gender in Commons debates from 1945 using computerized text mining. We make three major discoveries. The first is that there is strong evidence to support the central feminist claim that women’s contributions to debates over these eight decades have been substantively different to those of male colleagues in ways that stretch beyond a greater attentiveness to gender itself. The second is that this effect has been weakening as the number of women in Parliament increased, most notably from the landmark 1997 election. Finally, we question the oft-made claim by scholars and politicians that, since the election of Margaret Thatcher in 1979, the Labour party has more consistently focussed on representing women in Parliament than the Conservatives.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it