MétaCan
Menu
Back to cohort
Record W7101043229

and the Work of Canadian Policy Consultants 2006–2013

2013· article· en· W7101043229 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)ExternalizationGovernment (linguistics)Public policySubject (documents)Perception
DOInot available

Abstract

fetched live from OpenAlex

Abstract: The nature of policy advisory systems and the capacity and influence of individual system actors has been a subject of much interest in recent years, especially vis-à-vis observed trends towards the twin themes of politicization and externalization of policy advice. Studies to date for the most part have focused only on the capacity of highly visible advisory system actors such as professional policy analysts in government or those in the NGO and business sectors. This study examines the role of the ‘shadow ’ or ‘invisible ’ actors employed by governments on temporary contracts as managerial or other kinds of policy consultants to undertake activities related to policy development and evaluation processes. The study reports on the findings of a 2012–2013 survey of such consultants in Canada and presents data on relevant aspects of their background, training, perceptions and capabilities compared to permanent policy analysts employed fulltime by governments. It finds most consultants to be better qualified than their permanent counterparts and to primarily engage, like the latter, in process-related policy work. This answers some questions about the roles and relationships of these members of the advisory system but raises other questions about where the ‘substance ’ of policies originates.

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)0.000
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: none
Teacher disagreement score0.839
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.278
Teacher spread0.259 · 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 designTheoretical or conceptual
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicPolicy Transfer and LearningFrench-language works237,207