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Record W4413087742 · doi:10.1002/cprt.32371

Public Welfare Foundation grants

2025· article· en· W4413087742 on OpenAlexaboutno aff

Bibliographic record

VenueCorporate Philanthropy Report · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsFoundation (evidence)WelfarePublic administrationPublic welfarePolitical sciencePublic economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Scope:The Unitarian Universalist Association of Congregations supports community organizing campaigns aimed at creating systemic change in the economic, social and political structures that affect the lives of those who have been excluded from resources, power and the right to determination.The organization is currently accepting applications for funding under its Fund for a Just Society program, which supports such projects that are less likely to receive conventional funding because of the innovative or challenging nature of the work or the economic and social status of the constituency.Deadline: Sept. 30.Funds: The maximum award is $15,000, but most grants range between $6,000 and $8,000.Eligibility: For this program, grants are made to non-Unitarian Universalist groups in the United States and Canada that use community organizing to bring about systemic change leading to a more just society; mobilize those who have been disenfranchised and excluded from resources, power and the right to self-determination; have an active focused campaign to create systemic change; and have an operating budget of less than $500,000.Areas: Priority is given to active, specific campaigns to create change in the economic, social and political structures that affect people's lives.The program does not fund social services, educational programs or advocacy-only projects.Nor does it make grants for training to individuals that is not connected to a campaign for justice.

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)0.001
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: none
Teacher disagreement score0.953
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.245
GPT teacher head0.406
Teacher spread0.161 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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