MétaCan
Menu
Back to cohort
Record W7028203547

The Efficacy and Challenges of Lobbying Regulation in Canada: A Comprehensive Analysis

2024· article· en· W7028203547 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaDemotionTSG101Articular cartilage damageGestational period
DOInot available

Abstract

fetched live from OpenAlex

Lobbying, often viewed skeptically and associated with corruption, plays a pivotal yet contentious role in modern governance. This paper examines the efficacy of Canadian federal lobbying legislation amid public disillusionment with governmental processes. While only 32% of Canadians express confidence in the Federal Parliament, concerns about lobbying's influence persist. Despite regulatory efforts, lobbying in Canada remains complex, with historical and political contexts shaping its regulation. This study undertakes a comprehensive investigation into Canadian federal lobbying legislation, exploring its ability to regulate lobbying activities effectively. It scrutinizes the regulatory framework, enforcement mechanisms, and identifies systemic barriers that impact trust, access, and perceptions of corruption within the Canadian political landscape. Analysis reveals a troubling trend of legislative stagnation punctuated by scandal-driven regulatory reforms. Despite recurrent scandals prompting regulatory reviews, meaningful reform is often delayed, perpetuating a cycle of distrust. Systemic barriers, including loopholes in registration requirements, disclosure deficiencies, and inadequate enforcement mechanisms, undermine transparency and accountability. Addressing these challenges necessitates closing loopholes, enhancing disclosure requirements, and providing adequate resources to regulatory bodies. Without meaningful reforms, the gap between lobbying regulations on paper and their implementation in practice will persist, threatening the integrity of Canada's political landscape.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.819

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.013
Science and technology studies0.0160.007
Scholarly communication0.0090.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.219
Teacher spread0.176 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueScholarship at UWindsor (University of Windsor)Same topicPolitical Influence and Corporate StrategiesFrench-language works237,207