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Record W2559455505 · doi:10.1016/j.polsoc.2016.11.001

The MPA/MPP in the Anglo-democracies: Australia, Canada, New Zealand, the United Kingdom, and the United States

2016· article· en· W2559455505 on OpenAlexaffabout
Leslie A. Pal, Ian D. Clark

Bibliographic record

VenuePolicy and Society · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of TorontoCarleton University
Fundersnot available
KeywordsConvergence (economics)Diversity (politics)Scope (computer science)KingdomPolitical scienceSociologyPolitical economyLawEconomicsEconomic growthComputer science

Abstract

fetched live from OpenAlex

Abstract Should one expect convergence among MPA/MPP programs around the world, and in particularly among programs in the “Anglo-sphere” or among the Anglo-democracies, defined here as Australia, New Zealand, Canada, the United Kingdom, and the United States. For reasons of shared history and language, one might expect convergence, but there are counter-arguments as well that note, for example, the rich diversity among American programs alone. The paper analyzes 99 programs drawn from among these countries to find an answer. The analysis is wider in scope and more granular than anything that has been done to date, with data that allow comparisons of: (1) subject matter emphasis between policy and management, (2) the amount of required quantitative content, and (3) program length (number of standardized courses required to graduate). After illustrating a standardized metric of comparison we show that the convergence hypothesis cannot be sustained. Our conclusion entertains several conjectures about why this might be the case.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.290
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.178
GPT teacher head0.452
Teacher spread0.274 · 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.

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

Citations14
Published2016
Admission routes2
Has abstractyes

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