Bibliographic record
Abstract
Public-sector capital, including infrastructure, is an important component of public expenditures. The stock of public capital comes in various forms. Some types of public goods are durable by their very nature. Defense spending, for example, includes not only military personnel but also equipment like weapons, tanks, airplanes, and ships. Virtually all public programs, including the provision of public services to citizens, require buildings and associated equipment. The public sector may also be involved to a greater or lesser extent in providing infrastructure for use by the private sector. Examples include transportation facilities (e.g., roads, bridges) and communications installations. As essential components of an efficiently functioning private sector, these forms of infrastructure are well known to contribute to productivity and growth. This chapter addresses the implications for fiscal federalism that result from the significant capital component to public goods and services. Acquisition of capital gives rise to special issues because of its durable nature. Current capital purchases result in both a stream of benefits and a need for maintenance and replacement in several periods into the future. This has two sorts of implications. First, the decision rules for providing public services must necessarily take account of this intertemporal aspect. Service provision requires not only current expenditures but also the building up of physical capacity to support this provision. Full account must be taken of the likely growth in demand for services in the future. This capacity will have to be maintained and replaced as it wears out.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".