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Record W2089588104 · doi:10.1057/iga.2012.4

Lobbying and transparency: A comparative analysis of regulatory reform

2012· article· en· W2089588104 on OpenAlexaboutno aff
Craig Holman, William V. Luneburg

Bibliographic record

VenueInterest Groups & Advocacy · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)DemocracyPolitical scienceGovernment (linguistics)Public administrationPoliticsPolitical economyLawSociology

Abstract

fetched live from OpenAlex

As citizens grow increasingly wary of whose interests are being represented in the public policy arena, especially in light of recent sensational scandals showing a cozy relationship between professional lobbyists and lawmakers, a crisis of confidence is engulfing many democratic societies across the European and North American continents. Public perceptions of undue influence peddling, in which special interest groups exercise too much sway over government for self-serving purposes, have led to growing demands for the regulation of lobbyists and transparency of the policymaking process. The United States and Canada have been struggling for decades to refine their systems of lobbyist regulation. Of all the shortcomings of the North American model of lobbyist regulation – and there are many – transparency is not, for the most part, one of them. Many European countries have also been experimenting with systems of lobbyist regulation. Until recently, however, the European national experiments have produced very different results among themselves and in comparison with the North American counterparts. Surprisingly, some of the earliest efforts to regulate lobbying occurred among new democratic countries in Eastern Europe rather than the more advanced industrial democracies of Western Europe. This observation stands in stark contrast to the North American experience, where lobbyist regulation emerged as an effort to manage a highly developed class of professional lobbyists within the strictures of long-standing democratic principles. The authors find that the answer to this anomaly lies in the fact that early European lobbyist regulations focused not on transparency as a means to regain public confidence in government, but on providing business interests with access to lawmakers as a means to bolster fledgling economies. This focus on access is quickly giving way to demands for transparency as many European governments, racked by scandal, are striving to salvage the public's trust. Propelled largely by example from a reluctant European Parliament and Commission, which are themselves attempting to convince Europe that a regional government is in its own interest, several European countries are beginning to make a transition from weak systems of lobbyist regulation, which emphasize business access, to strong systems of lobbyist regulation, which emphasize public transparency. In order to discern ‘best’ practices for achieving transparency through lobbying regulation, the authors first chart the regulatory systems of the United States and Canada. That is followed by an analysis of all of the European lobbying regimes. The oft-expressed objection to this new trend toward transparency in Europe – that professional lobbyists view such regulations as overly burdensome – is undercut by research on European and American lobbyists’ attitudes toward regulation, which are generally quite favorable. Like everyone else, lobbyists realize that they have an image problem and that the best way to address that problem is by operating in the broad daylight of public transparency. Finally, the authors offer recommendations on how to enhance transparency in policymaking, drawing from detailed comparisons of the North American and European models of lobbyist regulation.

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)0.017
metaresearch head score (Gemma)0.049
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0040.008
Scholarly communication0.0090.006
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.075
GPT teacher head0.296
Teacher spread0.222 · 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

Citations132
Published2012
Admission routes1
Has abstractyes

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