The Boundaries of Property: Complexity, Relationality, and Spatiality
Bibliographic record
Abstract
The boundary is crucial to property interactions, yet we know little of how it works in the everyday world. Merrill and Smith provide an influential set of hypotheses in this regard, characterizing the boundary as a device for communicating simple messages of exclusion. The first goal of this paper is to assess these claims. Drawing from qualitative data on gardening and property from a neighbourhood in Vancouver, I suggest that the messages of the boundary may also be complex, intersubjective, and ambiguous. The supposed robust moral intuitions that inform people’s interactions with boundaries are not always exclusionary. Boundaries are spaces of connection, as well as lines of separation. Secondly, drawing from the sharp distinction between the heterogeneity of the empirical record and the studied simplicity of Merrill and Smith’s account, I make some broader claims regarding property and the boundary. Rather than seeking universality, simplicity and singularity, I suggest the necessity and value of working with complexity. A relational view of property and space (or ‘spatiality’), I suggest, offers us a better perspective in which to begin to think about the complex work of the everyday property boundary.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.062 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".