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Record W2341785460

Rights and Queues: On Distributive Contests in the Modern State

2016· article· en· W2341785460 on OpenAlexaboutno aff
Katharine Young

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsDistributive propertyState (computer science)Political scienceLaw and economicsDistributive justiceLawMathematical economicsEconomicsComputer scienceMathematicsEconomic JusticeAlgorithmPure mathematics
DOInot available

Abstract

fetched live from OpenAlex

Two legal concepts have become fundamental to questions of resource allocation in the modern state: rights and queues. As rights are increasingly recognized in areas such as housing, health care, or immigration law, so too are queues used to administer access to the goods, services, or opportunities that realize such rights, especially in conditions of scarcity. This Article is the first to analyze the concept of queues (or temporal waiting lines or lists) and their ambivalent, interdependent relation with rights. After showing the conceptual tension between rights and queues, the Article argues that queues and “queue talk” present a unique challenge to rights and “rights talk.” In exploring the currency of rights and queues in both political and legal terms, the Article illustrates how participants discuss and contest the right to housing in South Africa, the right to health care in Canada, and the right to asylum in Australia. It argues that, despite its appearance in very different ideological and institutional settings, the political discourse of “queues” and especially “queue jumping” commonly invokes misleading distinctions between corruption and order, markets and bureaucracies, and governments and courts. Moreover, queue talk obscures the first-order questions on which resource allocations in housing, health care, or immigration contexts must rely. By bringing much-needed complexity to the concept of “queues,” the Article explores ways in which general principles of allocative fairness may be both open to contestation and yet supportive of basic claims of rights.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.052
GPT teacher head0.345
Teacher spread0.293 · 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 designTheoretical or conceptual
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

Citations28
Published2016
Admission routes1
Has abstractyes

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