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Property as Abstraction

2009· article· en· W2080475097 on OpenAlexaff
Nicholas Blomley, Janet C. Sturgeon

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHumanitiesFallacySociologyPhilosophyContext (archaeology)EthnologyEpistemologyHistory

Abstract

fetched live from OpenAlex

Abstract Haila questions the dominant ‘story’ that ‘imperfections’ in Chinese urban land markets can only be resolved through state sanctioned private property rights. She interrogates the meaning of concepts such as ‘market’ or ‘property’, wary of the ‘ontological fallacy’ in which concepts are confused for real objects. Drawing from Mitchell (1991 ), we seek to take this farther, by tracing how a distinction between property as representation and as reality is produced, and seeking to evaluate the effects this divide has on social practice. Rather than treating property in the Chinese context as an abstraction, we urge scholars to be alive to its empirically and ethically diverse manifestations. Résumé Haila conteste le ‘récit’ dominant selon lequel les ‘imperfections’ des marchés fonciers urbains chinois ne peuvent se résoudre que par des droits de propriété privée cautionnés par l'État. Elle interroge la signification de concepts tels que ‘le marché’ ou ‘la propriété’, se méfiant de ‘l'illusion ontologique’ où l'on confond concepts et objets réels. Partant des travaux de Mitchell (1991), nous prolongeons cette idée en décrivant la distinction qui s'établit entre la propriété comme représentation et la propriété comme réalité; sont aussi évalués les effets de cette différenciation sur la pratique sociale. Au lieu de traiter la propriété dans le cadre chinois comme une abstraction, nous invitons les chercheurs à prendre conscience de la diversité de ses manifestations tant sur le plan empirique que sur le plan éthique.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.168

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.438
Teacher spread0.350 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2009
Admission routes1
Has abstractyes

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