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Record W1608137855 · doi:10.22230/cjnser.2013v4n2a148

Social Impact Bonds: The Next Phase of Third Sector Marketization?

2013· article· en· W1608137855 on OpenAlexaffvenueabout
Meghan Joy, John Shields

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAusterityMarketizationPublic sectorPoliticsRecessionBondTertiary sector of the economyEconomicsEconomic growthBusinessPolitical scienceEconomyFinanceChina

Abstract

fetched live from OpenAlex

The politics of austerity has pushed the third sector to the centre of attention as governments turn to non-governmental institutions to pick up the social deficits created by economic recession and the state’s retreat from social provision. Some governments have begun supporting alternative service funding through such innovations as social impact bonds (SIBs), a financial product used to encourage the upfront investment of project-oriented service delivery. This paper provides a clearer understanding of what SIBs are and traces their emergence within Canada while linking them to their cross national origins. SIBs are situated conceptually within broader contemporary developments within the non-profit sector, particularly the agenda of public sector reform and third sector marketization. The analysis focuses on the potential impact of SIBs on non-profit policy voice and capacity to represent and meet diverse community needs as it is this function that to a significant degree defines the third sector’s ability to be innovative.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.841
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0150.014
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.001

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 head0.195
GPT teacher head0.374
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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

Citations110
Published2013
Admission routes3
Has abstractyes

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Same venueCanadian journal of nonprofit and social economy researchSame topicCommunity Development and Social ImpactFrench-language works237,207