MétaCan
Menu
Back to cohort
Record W2769052923 · doi:10.1097/nna.0000000000000557

Social Return on Investment

2017· article· en· W2769052923 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJONA The Journal of Nursing Administration · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInvestment (military)BusinessEconomicsPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether the methodology of social return on investment (SROI) could be a way in which the value of a healthcare-related program (children's cancer camp) could be captured, evaluated, and communicated. BACKGROUND: The value of healthcare goes beyond what can be captured in financial terms; however, this is the most common type of value that is measured. The SROI methodology accounts for a broader concept of value by measuring social, environmental, and economic outcomes and uses monetary values to represent them. METHODS: The steps/stages of an SROI analysis were applied to the context of a children's camp for this article. RESULTS: Applying the SROI methodology to this healthcare-related program was feasible and provided insight and understanding related to the impacts of this program. CONCLUSIONS: Because of SROI's flexibility, it is a tool that has great potential in a healthcare environment and for leaders to evaluate programmatic return on investment.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.708

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 head0.194
GPT teacher head0.367
Teacher spread0.173 · 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