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Record W1927131673 · doi:10.1111/capa.12065

Making the invisible public service visible? Exploring data on the supply of policy and management consultancies in<scp>C</scp>anada

2014· article· en· W1927131673 on OpenAlexaff
Michael Howlett, Andrea Migone

Bibliographic record

VenueCanadian Public Administration · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsInstitute of Public Administration of CanadaSimon Fraser University
Fundersnot available
KeywordsTransparency (behavior)AccountabilityBusinessOligopolyNorm (philosophy)Contract managementService (business)MarketingEconomicsComputer securityMicroeconomicsCournot competitionComputer science

Abstract

fetched live from OpenAlex

Abstract The use of external policy and management consultants in government has been receiving increasing attention in many countries, includingCanada. We explore new data on management consulting compiled from information released since the creation of theFederalAccountabilityAct to address the supply side of contracting. We find several large multi‐year contracts have taken up a larger percentage of contracting activity while the number of smaller contracts has declined. The data suggest a pattern of oligopsonic demand concentrated mostly in a handful of very heavy users and an increasingly oligopolistic supply pattern where less than 5% of companies accounted for 80% of total contract values and where repeat contracts are the norm. Measures of accountability and transparency need to extend to the “invisible” public service of contract consultants.

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)0.003
metaresearch head score (Gemma)0.035
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.017
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.224
GPT teacher head0.374
Teacher spread0.150 · 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

Citations36
Published2014
Admission routes1
Has abstractyes

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