‘Stable and Four-Square:’ A Colonial History of Property-Owning Democracy
Bibliographic record
Abstract
This paper explores the colonial history of the theory of ‘property-owning democracy.’ Focusing on R.R. Torrens’ title registration system, the paper links property-owning democracy to nineteenth-century debates on land rights and title registration. Instituted in South Australia in 1858, Torrens’ system linked the simplification of transactions in land to visions of a property-owning society. Seeking to replace complex land laws, Torrens’ system’s emphasis on speeding up land transactions appealed both to settler society and metropole. This transformation facilitated the dispossession of Indigenous lands and intertwined property law with colonial narratives of progress, liberty, and democracy. Ultimately, Torrens’ vision identified democracy with a new property regime securing the future of property title and political rights. Through a common engagement with nineteenth-century Britain’s ‘land question,’ Torrens’ project in South Australia is linked to the development of the twentieth-century political concept of property-owning democracy. The paper makes the case that exploring land registration debates reveals the importance of secure property rights and human capital in the history of ideas of property-owning democracy. Legal and bureaucratic innovations like the property register were considered to free individuals to invest in their own economic development and create the economic conditions for democracy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".