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Record W4404443702 · doi:10.1093/ppmgov/gvae010

Reconceptualizing Administrative Burden Around Onerous Experiences

2024· article· en· W4404443702 on OpenAlex
Pierre‐Marc Daigneault

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePerspectives on Public Management and Governance · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversité Laval
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBusinessPublic relationsMarketingPublic administrationPublic economicsPolitical scienceSociologyEconomic growthEconomics

Abstract

fetched live from OpenAlex

ABSTRACT Despite ongoing discussions on the need to improve the conceptualization and measurement of administrative burden, several conceptual problems remain. This study offers the first systematic analysis and evaluation of this increasingly central public management concept. Using an ontological-semantic approach, I show that the current conceptualization fails to fully and directly account for individuals’ onerous experiences. I address five interrelated issues, including the overlap of cost categories and the conflation of state actions with onerous experiences. While psychological costs should be retained, I argue for abandoning the other cost categories. Building on previous reconceptualization efforts, I propose a new framework focused on time, money, effort, and psychological costs. Additionally, I explore the structure of the concept and propose specific indicators for each dimension. I then discuss the independence of these dimensions, their capacity to reflect the distributive nature of burdens, and avenues for empirical validation.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.096
GPT teacher head0.427
Teacher spread0.331 · 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