ANTICORRUPTION POLICY IN CANADA AND KAZAKHSTAN: BOTTOM-UP VS. TOP-DOWN AGENDA SETTING
Bibliographic record
Abstract
In this paper, we will investigate the process of agenda setting in Canada and Kazakhstan with regard to anti-corruption policy. A comparative analysis of anti-corruption policies in countries with absolutely different historical, political, economic and cultural traditions like developed liberal-democratic state Canada and young developing Central Asian Republic - Kazakhstan seems at the first view, bizarre and casual. However, taking into account the assumption of public policy analysts Jenson and Stark that “the policy making agenda is created out of the history, traditions, attitudes and beliefs…”[1] present comparative cross-nation analysis allows not only to reveal similarities and divergences in anti-corruption initiatives and policies of both states, but to define and analyze how the agenda-setting behavior essentially differs in present countries, depending on type and nature of the political regime. Keywords: Agenda-setting, Canada, Kazakhstan, anti-corruption [1] JENSON, 1991; STARK, 1992 in M. HOWLETT M and M. RAMESH and A.PERL, “Studying Public Policy Circles and Policy Subsystems”, Oxford/NewYork: Oxford University Press. 2009, p. 98
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".