Tax Policy Trends: Implication of a Biden win for US corporate tax policy and competitiveness
Bibliographic record
Abstract
With the upcoming U.S. election in November the potential for a dramatic change to corporate taxes in the U.S. is a real possibility.This would follow close on the heels of the 2018 overhaul of the U.S. corporate and personal tax system under the Tax Cuts and Jobs Act (TCJA).Biden's plan would ostensibly be enacted in 2021-following a successful bid for the presidency-and would lift the U.S. large corporate rate to 28%, partially unwinding the rate reduction enacted in the TCJA that saw the U.S. large corporate rate fall from 35% (1993-2016) to 21%. 1 As shown in the graph, this would raise the current U.S. marginal effective tax rate on large corporations from 22.6% in 2020 to 25.4% in 2021, reducing U.S. investment and productivity.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".