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Record W4313440681 · doi:10.29173/cjnser604

Common Approach to Impact Measurement: Four Community-Driven Flexible Standards for More Interoperable Impact Data

2022· article· en· W4313440681 on OpenAlexaffvenue
Katherine Ruff, Valerie Adriaanse, Alicia Richins, Garth Yule

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsCarleton University
Fundersnot available
KeywordsInteroperabilitySet (abstract data type)Computer scienceBusinessData scienceKnowledge managementEngineeringWorld Wide Web

Abstract

fetched live from OpenAlex

Common Approach to Impact Measurement (Common Approach) is a set of four flexible impact measurement standards designed to empower charities, nonprofits, coops, social purpose businesses (collectively referred to as social purpose organizations or SPOs), and those they serve to identify which impacts are most meaningful. These standards are not designed to make measurement more rigorous or more accurate; rather, they make measurement more useful and interoperable, and, eventually, more attuned to the priorities of those impacted.

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)0.015
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.460
GPT teacher head0.417
Teacher spread0.043 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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