Systemic Altruism
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Justice & public goodsPreliminary editorial review

data.org

Supports social-impact organizations with data and AI skills, resources, convenings and a Data Maturity Assessment.

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Systemic Altruism practice potential: 70–80/100
90% of weighted axes reviewed. A mechanism hypothesis, not proven effectiveness or a donation recommendation.

Who this work enables

Tools & support for charities: A reusable data-capacity assessment, guides and training for social-impact organizations.

Humanity’s Checklist source match

Gatekeepers · Coordination — editorial, partial alignment.

The model distributes data capability and connects expertise, resources and social-impact teams; this is editorial alignment, not a verified affiliation.

Explicit checklist adoption: not verified. A mechanism match is not an affiliation, endorsement, evidence of effectiveness or a scoring bonus. Read the practice.

Focus classification: 2026-10-27. Based on the organization’s dated official sources below; earlier axis-review dates are unchanged.

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The proposed pathway

Social-sector data capacity and reusable assessment tools

Six dimensions, with rationale

Structural depth

3 / 4

Addresses recurring organizational data capability and governance constraints rather than only delivering one direct program.

Institutional reach

4 / 4

Its documented work crosses public health, climate and financial inclusion through a global partner model.

Durability

2 / 4

Workforce skills and organizational practices may persist, while staff turnover and technical change require continuing support.

Scalability

3 / 4

An assessment framework and resource library can be reused, but training and effective implementation remain resource-dependent.

Funding additionality

Unreviewed

Unknown: a current marginal funding gap, counterfactual and delivery capacity have not been audited.

Community agency

Unreviewed

Unknown: participation, open access or stated values do not establish audited consequential decision rights for affected communities.

Evidence and selection

Organization reported; documented official mechanism

Illustrative inclusion to examine this mechanism. Inclusion is not an external recommendation or a verified comparative ranking.

A testable next question

Do participating organizations sustain better-governed data use and improved mission outcomes relative to appropriate alternatives, including the option not to deploy AI?

Review confidence: Moderate for documented design; low for systemic attribution. Documented data-capacity and assessment-tool mechanism; not an independent evaluation of grantees or innovation-challenge winners.

What remains uncertain

An assessment score or trained practitioner count is not a causal outcome measure. AI adoption can introduce bias, privacy risks and unnecessary complexity; partner results require separate review.

Sources to inspect

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Axis review: 2026-10-27 · weighting method v0.2 (2026-10-26) · Method, conflicts and coverage