Still budgeting by muddling through: Why disjointed incrementalism lasts
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
Abstract This paper examines Charles Lindblom’s ‘science of muddling through’ and its transport and transformation to budgeting through the work of Aaron Wildavsky by analyzing its impact on budget theory and assessing its continued relevance to the practice of budgeting in the context of the Canadian federal government. We find that: the concept is of fundamental importance and yet considerably elastic to capture key features of political, economic, and organizational life; the criticisms of it have been overstated although, perhaps surprisingly, with the exception of budgeting, little empirical testing of the concept has been undertaken; the impact on budget theory and practice has been considerable especially since much of the initial application was undertaken at a time of relative economic and political stability in government and in budgeting; and yet even today, in a more turbulent world, the concept remains surprisingly relevant, although not complete, for understanding and explaining some of the most central and enduring features of budgetary behaviour. It is a key to our understanding of how budget participants deal with complexity and manage conflict.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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