Bibliographic record
Abstract
Today, issues of establishment or quasi-establishment are topical and contentious in Australian public discourse. In the decades following the invasion and white settlement of Australia debate raged about the proper relationship between church and state in the fledgling Australian colonies. In this paper we review Australia’s past (1788 to 1850) to investigate whether and how interreligious relations demonstrate different forms of competition and conflict. Specifically, we explore how the political and social development of Australian colonies produced a quasi-establishment – neither true establishment nor strict separation of church and state – with rather different outcomes for church authority and practice. We suggest that changes in inter-group relations in an open playing field have led to new exertions of competition and conflict for establishment or quasi-establishment in Australia 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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.015 | 0.025 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.083 | 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".