Bibliographic record
Abstract
Canadian and Australian girls’ fiction of the early twentieth century contains surprising differences in feminine ideals with respect to education and work. In Chapter 4, Ken Gelder and Rachael Weaver explain that the question of a young women’s career in post-federated Australia ‘saw a convergence of narratives that each competed for relevance along very specific lines of argument: to do with propriety... job security, reasonable rates of incomes and expectations of career advancement, working conditions, and, in each case, the impact or effect these things might have on femininity and the role it plays in the nation’s future’. 1 This same question remains central to girls’ fiction in both Canada and Australia in this period. Girls’ fiction in these white settler colonies has many similarities, containing strong ideals related to domesticity, education, employment and femininity. The question of a girl’s occupation and the skills she needs to become a successful young woman is central to these texts. The important differences are based on education, in which the Canadian attitudes towards women’s higher education and employment are generally much more positive. Although Canadian girls’ texts also typically conclude with marriage (and presumably motherhood), Canadian girls like L.M. Montgomery’s Anne of Green Gables and Nellie McClung’s Pearlie Watson are offered the opportunity to pursue higher education and use this education to teach others. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".