Lobbying and uncertainty: Lobbying's varying response to different political events
Why this work is in the frame
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Bibliographic record
Abstract
Does political uncertainty affect whether lobbyists contact government officials? We suggest that the answer depends on the type of uncertainty introduced. Distinguishing between policy objective uncertainty—where organized interests and lobbyists are uncertain about the policy intentions of decision makers—and issue information uncertainty—where policymakers are uncertain about the technical details of issues—we hypothesize that whereas an increase in policy objective uncertainty leads to a decrease in lobbying, a rise in issue information uncertainty leads to more lobbying. We test the hypotheses with longitudinal data from the Canadian Lobbyists Registry measuring change in the number of times lobbyists have contacted government ministries each month from 2008 to 2018. The results suggest that lobbying intensity does respond differently to these types of uncertainty. Whereas events introducing issue information uncertainty have a statistically significant positive relationship with lobbying, events introducing policy objective uncertainty do not.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it