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Record W185977203

ENGAGING DIASPORA COMMUNITIES IN' DEVELOPMENT: AN INVESTIGATION OF FILIPINO HOMETOWN ASSOCIATIONS IN CANADA

2006· dissertation· en· W185977203 on OpenAlexaboutno aff
Jon Silva

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
FundersUnited Nations Population FundUnited States Agency for International Development
KeywordsOutreachDiasporaTransaction costBusinessDatabase transactionPublic relationsFocus groupEconomic growthPolitical scienceMarketingFinanceEconomics
DOInot available

Abstract

fetched live from OpenAlex

The study examines the potential role that donor agencies may have in facilitating the flow of group donations called collective remittances among migrant organisations, which fund development projects in their home communities. It focuses on Filipino hometown associations (HTAs) in Canada and the barriers that prevent then1 from sending resources to the Philippines regularly. The study draws information from three sources: a literature review of diaspora philanthropy, a survey of Filipino HTAs and interviews of stakeholders. The analysis reveals that high transaction costs are the major factor contributing to the sporadic exchanges of resources. Transaction costs occur due to limited exchanges of information, which leads to greater risk and uncertainty for stakeholders at both the 'giving' and 'receiving' ends of the transaction. The study recommends that donor assistance should focus on capacity building to give stakeholders in the Philippines the opportunity to improve their communication and outreach strategies.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0390.007
Scholarly communication0.0060.002
Open science0.0020.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.238
Teacher spread0.216 · 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 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

Citations14
Published2006
Admission routes1
Has abstractyes

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