MétaCan
Menu
Back to cohort
Record W1965708196 · doi:10.1177/0899764008316056

Sociodemographic and Personality Characteristics of Canadian Donors Contributing to International Charity

2008· article· en· W1965708196 on OpenAlexaboutno aff
Suja S. Rajan, George H. Pink, William H. Dow

Bibliographic record

VenueNonprofit and Voluntary Sector Quarterly · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsReligiosityHigher educationPersonalityFeelingPoliticsDemographic economicsBiology and political orientationPolitical scienceSocial psychologyPsychologyEconomics

Abstract

fetched live from OpenAlex

This study aims to establish a sociodemographic and personality profile of Canadians who donate internationally, fills the gap in the literature with regard to individual-level determinants of international giving, and compares these determinants with those of domestic donors. Women, volunteers, and individuals of non-Canadian origin, with higher income, higher education, higher level of religiosity, higher political awareness and participation, and higher frequency of extended family participation were more likely to contribute internationally. Higher education and a higher level of religiosity seem to influence international giving more than they did domestic giving. In terms of the variations in amount of international donations the important determinants are income, education, level of religiosity, and feeling of financial security. These results suggest that international charities should probably target their efforts at more-educated, higher-income and more-religious individuals. The other target donors are volunteers, women, individuals of non-Canadian origin, and politically aware and socially involved individuals.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.751

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 studies0.0010.000
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 head0.031
GPT teacher head0.262
Teacher spread0.231 · 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 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

Citations63
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueNonprofit and Voluntary Sector QuarterlySame topicNonprofit Sector and VolunteeringFrench-language works237,207