Analysis of the Corporate Behaviors after the Corporate Tax Cuts with Respect to Job Creation: A Preliminary Study of Select Corporations in the United States of America
Bibliographic record
Abstract
A preliminary study of the impact of tax cuts on job creation was done by studying a random sample of 12 largest corporations selected from the Fortune 500 companies. The Annual Reports of the 12 sample companies pre-tax cut and post-tax cut periods were downloaded, and figures tabulated for revenues, property, plant, and equipment (PPE) as well as employees reported by those companies for both the periods. We found that the revenue increased by an average of 7.78 percent which showed signs of growth in those companies, but the investment in PPE by the companies during the same period increased at an average of only 0.32 percent, which indicated that the companies did not divert the resources they saved in taxes to add capacity. Therefore, the potential for jobs growth was nonexistent or minimal. Another indicator showed the same outcome as the companies reported their workforce reduced since 2017 by an average of 0.54 percent.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".