MétaCan
Menu
Back to cohort
Record W4400319621 · doi:10.1080/14719037.2024.2369789

New public management marketizers versus Neo-Weberian state modernizers? Institutional configurations of social impact bond utilization among 18 OECD countries

2024· article· en· W4400319621 on OpenAlexaff
Jesse Hajer, Bin Chen

Bibliographic record

VenuePublic Management Review · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsState (computer science)Public managementPolitical scienceBondNew public managementInstitutional theoryEconomicsPublic economicsPublic administrationEconomic systemBusinessPolitical economyPublic sectorFinanceManagementLaw

Abstract

fetched live from OpenAlex

Social Impact Bonds (SIBs), a New Public Management (NPM)-style commissioning model, contain elements of other reform framings, widening their appeal and potential for variation in differing reform contexts. This study implements a fuzzy-set qualitative comparative analysis (fsQCA), seeking configurations explaining SIB uptake across 18 OECD countries. The two high-utilization configurations produce an Anglo-American model of NPM marketizers and a European model of Neo-Weberian State (NWS) modernizers, whereas the four low-utilization configurations include exclusively NWS modernizers and maintainers, suggesting SIBs as a fertile case study of public management reform tools adapting and trajectories merging in differing national administrative cultures and contexts.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.005
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.116
GPT teacher head0.325
Teacher spread0.209 · 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 designObservational
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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePublic Management ReviewSame topicCommunity Development and Social ImpactFrench-language works237,207