The Problem of Partisan Experts and the Potential for Reform through Concurrent Evidence
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Bibliographic record
Abstract
I. INTRODUCTION 2II. THE PROBLEM OF EXPERT BIAS 3A . Payment of Experts Leads to Biased Testimony 6B. Partisan Preparation of Experts Leads to Biased Testimony 11C. Lack of Jury Competence and Limited Access to Expert 's Background Contribute to the Problem of Expert Bias .... 14D. Perceived Bias Breeds Contempt for Expert Witnesses .... 1 6E. Lack of Uniform Ethical Guidelines Creates Environment for Biased Testimony 18III. FAILED EFFORTS AT REFORM IN THE UNITED STATES 20A. Frye and Daubert 20B. Court-Appointed Experts and Other Failed Efforts at Reform 251. Science Courts and Expert Judges 252. Court-Appointed Experts 26a. Reasons Against Using Court-Appointed Experts 291. Lack of Necessity 292. Respect for the Adversarial System 303. Impracticality 324. The Availability of Technical Advisors 33IV. FOREIGN MODELS FOR DEALING WITH EXPERT BIAS 36A. Typical Civil Law (Inquisitorial) Systems 361. German Use of Court- Appointed Experts 362 . French Use of Court- Appointed Experts 403. Italian Use of Court- Appointed Experts 44a. Civil Proceedings 44b. Criminal Proceedings 454. German, French, and Italian Systems Do Not Provide Useful Models for Reform of U.S. Courts 46B. Adversarial Legal Systems 511. English System 512. Canadian System 53a. Federal Court 53b. Provincial Courts 54V. AUSTRALIAN USE OF CONCURRENT EVIDENCE MAY PROVIDE A MODEL FOR EFFECTIVE REFORM IN U.S. COURTS 55A. Problem of Expert Bias in Australian Courts 57B. The Concurrent Evidence Procedure 59C. Supplemental Reforms 60D. Benefits of Concurrent Evidence 61VI. CONCLUSION 63I. INTRODUCTIONIn the United States, expert witnesses are selected, paid, and prepared by the parties to the litigation. In this Article, we will explain why this system often leads to biased and partisan testimony from experts and explore several possible options for reform.In Part II, we will examine how the American adversarial system and its allowance for party payment and preparation of expert witnesses lead to an inevitable and unavoidable danger of partisan bias in expert testimony. We will also explain why this problem is exacerbated by a lack of jury competence in evaluating expert testimony and has led to contempt for experts amongst lawyers, judges, and those professional groups from which experts are often chosen. Finally, we will show that the lack of uniform ethical guidelines for testifying experts opens the door to biased testimony.In Part III, we will demonstrate that, although the problem of expert bias has long been recognized, past efforts for reform have been either ignored or proven inadequate. We will focus a large portion of this section on the widespread call for an increase in the use of court-appointed experts as well as some of the reasons that this practice has not become more prevalent.In Part IV, we will explore the possibility of American courts adopting a system akin to those in the civil law universe of continental Europe, including the regimes used in Germany, France, and Italy, whereby expert witnesses are appointed by the courts. These systems aim for neutral and independent expert testimony. We will argue that the use of court-appointed neutral experts - with some modifications which acknowledge the imperatives of the adversarial system - might provide a model for effective reform. We will then turn to the adversarial systems of England, Canada, and Australia. Despite sharing a legal tradition with the United States, we will show that the English system offers relatively little that could improve the use of expert witnesses in this country, but that the procedures used in the Canadian provincial system offer some intriguing ideas for reform. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it