MétaCan
Menu
Back to cohort

España: primer contribuyente del Banco Interamericano de Desarrollo en financiación no reembolsable

2012· article· es· W139908201 on OpenAlexaboutno aff
Ana María Martínez Jérez

Bibliographic record

VenueBoletín económico de ICE, Información Comercial Española · 2012
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Espana es el primer contribuyente del BID en financiacion no reembolsable. En el periodo 20092011, Espana aporto en su conjunto 615 millones de USD de financiacion no reembolsable, ampliamente por delante de Canada (105,5 millones de USD); Corea (34 millones de USD) y Japon (26,7 millones de USD), integrando estos cuatro paises el grupo de los principales donantes del BID. Desde un punto de vista geografico, en el quinquenio 2007-2011, Canada concentra el 83 por 100 de su financiacion no reembolsable en Haiti, tal concentracion no se da en ninguno de los otros tres paises, cuya financiacion no reembolsable se destina a un abanico de paises mas amplio. En el caso de Espana, el 80 por 100 de la financiacion no reembolsable se ha destinado a proyectos en 6 paises (Paraguay, Bolivia, Peru, Haiti, Guatemala, Republica Dominicana) y regionales, de los cuales 5 paises son considerados paises pequenos y vulnerables con un PIB de menos de 55.000 de USD; por el contrario, en Corea y Japon, la financiacion no reembolsable se ha destinado a proyectos en paises con un nivel superior de desarrollo: Brasil, Colombia, Mexico y Peru, los cuales absorben el 28 por 100 y 38 por 100 de la financiacion no reembolsable de Corea y Japon, respectivamente. Desde el punto de vista sectorial, en el quinquenio 2007-2011, se observa que Canada, Japon y ESPANA: PRIMER CONTRIBUYENTE DEL BANCO INTERAMERICANO DE DESARROLLO EN FINANCIACION NO REEMBOLSABLE Ana Maria Martinez Jerez*

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.136
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueBoletín económico de ICE, Información Comercial EspañolaSame topicPublic-Private Partnership ProjectsFrench-language works237,207