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Record W3007723731 · doi:10.1080/0967828x.2020.1727297

Diaspora and development beyond the state: the case of <i>Gawad Kalinga</i> in the Philippines

2020· article· en· W3007723731 on OpenAlexaff
Philip F. Kelly, Arnisson Andre C. Ortega

Bibliographic record

VenueSouth East Asia Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsYork University
Fundersnot available
KeywordsDiasporaPovertyEconomic growthState (computer science)SociologyPolitical scienceCommunity developmentVisionGender studiesEconomics

Abstract

fetched live from OpenAlex

Since 2000, Gawad Kalinga (GK) has emerged as a prominent player in promoting diaspora-driven strategies for social and economic development in the Philippines. GK has its roots as the social ministry of a Catholic lay organization that started by providing housing and youth programmes for the urban poor, but in recent years, it has moved towards a more secular model of fostering social entrepreneurship. Nevertheless, a distinctly moral imperative still underpins GK’s work, both in soliciting donations and volunteerism, and in selecting and supporting its development beneficiaries. A significant portion of GK’s funds, and volunteer labour, comes from the Filipino diaspora. This paper raises questions concerning the model of social and economic development that GK represents. In particular, we examine the drawbacks of private charitable involvement in the execution of state responsibilities such as social housing and poverty alleviation; and we ask what forms of moral subjectivity are created and populated in this model of development and how does it select, socialize and discipline beneficiaries? More broadly, this paper argues that the GK case addresses some of the promises and pitfalls of diaspora-driven development visions.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.096
GPT teacher head0.369
Teacher spread0.274 · 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 designQualitative
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

Citations5
Published2020
Admission routes1
Has abstractyes

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