'Still waters run deep': empirical methods and the migration patterns of regional publishers' authors and titles within Australian literature
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 the recent book London was full of rooms, Carol Hetherington argues that the “statistical basis for the London-centric view of Australian literary production is misleading” (Hetherington 245). This account, though, when held against the bibliographic evidence that it examines, at least in AustLit’s current dataset, is itself incomplete. As might be observed in the graph representing the place of publication of first-edition Australian novels around the world, for the period 1900–2000, the next largest publisher of Australian fiction after London, the United States, is less than one quarter the size of the total British production of Australian novels. The historical focus on London as Richard Nile’s and David Walker’s “mythologized literary center” appears borne out from such numerical comparisons, not challenged.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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