Bibliographic record
Abstract
This article documents the increased use of long and substantive preambles in federal legislation from 1985 to 2000. Only nine statutes had such preambles in the first five years of this study, while in the last five years, twentynine statutes did. Preambles were most frequently included in legislation arising from intergovernmental agreements, symbolic legislation, ideologically charged amendments of criminal and environmental laws, and legislation enacted in reply to court decisions. Plato suggested that preambles should persuade citizens to obey important laws by speaking to their hearts and minds through both reason and poetry. The author contends that this ideal is not met by contemporary preambles. Though preambles are often included in important legislation, they rarely speak directly to citizens as they do not use popular language or a persuasive voice. Various political uses of preambles are examined and the author concludes that contemporary preambles often seek to establish legitimacy by providing a narrative of the origins and purposes of the legislation. The professional uses of preambles are also examined, particularly the role of preambles in statutory and constitutional interpretation and in dialogues between the legislature and courts. The author concludes that while preambles have frequently oversold legislation and have been excluded from working versions of the law, they should still be included in important laws to better outline the purposes and processes which led to the enactment of the legislation and better communicate with the multiple audiences of modern legislation.
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".