Bibliographic record
Abstract
This dissertation is an examination of the nature and effects of legislative tenure. Specifically, I analyze the role of tenure at the federal level, in the United States Congress. The first chapter provides a background on nature of legislators and the roles that United States Congressmen play in the American economy, the three main questions that this dissertation looks to address, and describes the unique dataset that belies this research. Chapter 2 is an in-depth analysis on the nature of accrued legislative tenure throughout the entire history of the United States Congress. The second chapter then explores possible explanations for the structural break to legislative tenure rates that occurred sometime in the last quarter of the 19th century. Ultimately, while the ability to regulate an economy and the United States Civil War are likely causes, the ability to tax-and-spend did not contribute to the initial upswing in accrued tenure rates. Chapter 3 analyzes the impact of federal spending on state economic performance in light of the variation in tenure between states' Congressional delegations. States that have more tenured delegations secure more federal money for their respective constituencies, and this increased level of federal funds causes a dampening effect upon state economic performance. The result is robust when considering alternative measures of federal spending, such as federal spending received net of federal taxes paid, and the ratio of federal spending received to federal taxes paid. Finally, due to the nature of the two-stage process, I provide a range of estimates for the marginal harm caused by having increasingly tenured Congressional delegations. Chapter 4 investigates the impact that increased tenure, both in absolute amounts and in increased dispersion, has upon legislative productivity. Increased amounts of tenure, as well as increased amounts of tenure dispersion, leads to a reduction in the quantity and an increase in the price of legislation produced. The effects are akin to a cartel. Chapter 5 concludes and discusses future areas of research interest.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".