The territorialization of property in land: space, power and practice
Bibliographic record
Abstract
To understand the crucial work of property in land in enforcing and sustaining relationships of power between people, it is necessary to analyse the particular manner in which property became territorialized. I focus here on one crucial moment in which this occurred – the reconception of the space of landed property in seventeenth century rural England – tracing three domains of practice – surveying, husbandry and law. These forms of expert knowledge did not simply record changes in property's reterritorialization, I suggest, but actively participated in its remaking. As an ‘interaction device’, territory helped reconstitute changing property relations. While drawing from previous geographies of property, these practices placed an increased importance upon a territorial exclusivity that centred on individual rights, most particularly the right of the individual to exclude others. As such, the legal and practical defence of territory became of more pressing importance. This shift relied on and helped sustain a particular logic of visualization and spatialization, I shall suggest. Increasingly, property became disentangled from a localized nexus of collectively organized relations, and became situated within wider networks of calculation and commodification. The geographies of property forged in this period continue to be important to contemporary life, framing power relations in particular ways. As such, they demand our attention.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.069 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".