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Record W4214918047 · doi:10.1177/0308518x221075351

Racial capitalism, coloniality and the financialization of Caribbean remittances

2022· article· en· W4214918047 on OpenAlexafffund
Beverley Mullings

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCaribbean history, culture, and politics
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFinancializationCapitalismCapital (architecture)DiasporaInvestment (military)Control (management)EconomicsFinancial capitalValue (mathematics)Development economicsFinanceBusinessMarket economyPolitical scienceHuman capitalPoliticsGeography

Abstract

fetched live from OpenAlex

Diaspora remittances are a faithful source of capital, a vital social safety net and a source of local economic investment for many households, communities and states across the Caribbean. But recent efforts by powerful interests to exercise control over these flows of capital are beginning to threaten the continuity and accessibility of this lifeline. As financial institutions, fiscally constrained governments and imperializing states have become increasingly attuned to the value of Caribbean remittances, so too have their efforts to gain control over the volume and flow of these private transfers of funds. For governments, remittances promise the possibility of access to funds that can be used to bridge finance gaps, and among financial institutions they offer opportunities to generate profits from the cross-border movement of money. But for imperializing states, remittances are increasingly viewed as a potential threat to their efforts to control the movement of money. I argue that these different and sometimes conflicting views of remittances reflect the complex forms of coloniality and racial subjugation that continue to reproduce economies of dispossession.

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 score0.959
Threshold uncertainty score0.698

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 studies0.0010.001
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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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

Citations20
Published2022
Admission routes2
Has abstractyes

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