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Record W6993157405

Notes from the periphery: finding more than (non)ownership in property law?

2021· article· en· W6993157405 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicProperty Rights and Legal Doctrine
Canadian institutionsnot available
Fundersnot available
KeywordsMateriality (auditing)Property (philosophy)AssertionIndigenousPublic propertyProperty lawPrivate propertyProperty rightsSpace (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

Property law structures the way we make decisions about how we live together and with the world around us. In doing so, it shapes, but is also shaped by, our relationships with the places we inhabit and encounter. Traditionally, non-owners are defined by their distance and exclusion from the primary legal relationship and their lack of enforceable interests. Yet, land use conflicts continue to arise because people routinely assert relationships with land and resources that they are not formally recognised as owning but with which they are deeply entangled. This chapter touches briefly on three examples: the relations of Indigenous Peoples with fee simple lands within Canada; Māori ownership of freshwater in Aotearoa New Zealand; and claims to public space made by unhoused persons. Though these people–place relations are shaped by their legal definition as non-owner relations, purportedly severed and obscured for legal decision-making, they continue to shape formal legal property relations. As such, they deserve recognition as more than peripheral to property law. This chapter traces the assertion of these ‘more-than-ownership’ relations as part of the necessary work of rebuilding a system of property that sustains us as relational beings embedded in the complex materiality of places.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.042
GPT teacher head0.289
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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