MétaCan
Menu
Back to cohort
Record W2806079335 · doi:10.1177/0042098018768483

Foreign in a domestic sense: Puerto Rico’s debt crisis and paradoxes in critical urban studies

2018· article· en· W2806079335 on OpenAlexaff
Heather Whiteside

Bibliographic record

VenueUrban Studies · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAusterityDebt crisisPolitical economyCapitalismScrutinyDebtPoliticsFinancial crisisPositive economicsEconomicsSociologyHistoryPolitical scienceKeynesian economicsLawMacroeconomics

Abstract

fetched live from OpenAlex

The 2017 Puerto Rican debt crisis is as instructive as it is sad, reflective of the familiar pressures of late modern capitalism (namely neoliberalisation, financialisation, crisis, and austerity) as well as its own unique dynamics percolating through four hundred years of colonialism and a century of legal subjugation to Washington, DC. Neither one-off explanations of fiscal crisis nor casual conflation with other cases suffice to adequately account for this, or any other, public sector debt crises. Puerto Rico is both foreign and domestic, it is neither state nor municipality but its bonds are treated as such, it reflects larger trends and is circumscribed by its own unique history, subtle economic explanations are matched by bald, large-P politics. Analytical conundrums such as these are confounding and lead to perennial, potentially circular and irresolvable, debate in the critical urban studies literature. This paper explores whether the possibility of using the philosophical notion of paradox – a situation where sound reasoning leads to incomplete, unsatisfying, or unexpected results or consequences – and Zeno’s famous paradoxes in particular, can serve as allegorical heuristics capable of provoking new theories, expectations, or assumptions in urban studies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.069
GPT teacher head0.314
Teacher spread0.245 · 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 designObservational
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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueUrban StudiesSame topicHousing, Finance, and NeoliberalismFrench-language works237,207