Bibliographic record
Abstract
Very slowly Australia is acquiring high quality histories of its immigrant groups: Anny Stuer's survey of the French in Australia is a welcome addition to this, as yet, not very large number.Many British people find the French an enigma -both in Europe and elsewhere.Dr. Stuer's work does much to clarify things for Australia though, even then, there remains a strange contrast.On the one hand there is the considerable impact of the French nation and culture on Australia, as may be seen in the fears aroused by French explorers at French moves in New Caledonia and the New Hebrides, by French becoming the main foreign language in Australian Schools, by the proliferation of cultural groups such as the Alliance Francaise or of French schools such as those of the Marist brothers: on the other hand is the fact that the French have never settled in Australia in large numbers, nothing like the Germans, Italian, Greeks and Yogoslavs.From 5,000 or so in 1961 -brought in by the gold rushes -numbers of French-born persons dwindled steadily to 2,200 in 1947, and have only recently risen to 6,600 in 1966 and 12,100 in 1976; compared with 285,000 Italian-born persons or 147,000 Yugoslav, this is small indeed.Though relatively few in number, however, the French made a notable impact -in the goldfields, in winegrowing, in the sciences and arts, in commerce and banking, in social life and entertainment.Sometimes they even formed small colonies -as in Sydney late last century.Mostly, though, they were widely dispersed and scattered, inter-mixed and inter-married considerably and were generally very different from French settlers in Quebec or Louisiana.The whole story is quite fascinating and Dr.Stuer writes it up clearly and well, at times in an amusing, almost piquant, manner.She is particularly to be congratulated on putting together such an interesting and coherent account from the scattered, and often very meagre, evidence available to her.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.100 | 0.001 |
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; both teacher heads agree on what is shown here.
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".