Stability and Punctuations in Public Spending: A Comparative Study of Budget Functions
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.
Bibliographic record
Abstract
This article provides a comprehensive analysis of stability and punctuations in public spending within and across two different countries—Denmark and the United States. The theoretical starting point is the classic model of budget incrementalism and Jones and Baumgartner's model of disproportionate information processing. First, despite the clear differences in institutional setup, we show that public spending spanning many decades in Denmark and the United States are characterized by a similar distribution of small-, medium-, and large-scale spending changes. What is more intriguing is that we show how this aggregate result obscures (1) substantial variation between categories of public spending and (2) similar tendencies within similar spending categories across the two countries. These findings suggest that we need to unpack the overall budgets for detecting the particular sources of stability and change in government spending. Hence, the article offers important comparative findings that not only challenge the empirical validity of classic budgetary incrementalism but also advocate an increased focus on more disaggregated spending dynamics than employed in previous studies of the model of disproportionate information processing.
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 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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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 it