Bibliographic record
Abstract
In my book, Financial Litigation: Quantifying Business Damages and Values,1 I provide a comprehensive list of suggestions (do’s and don’ts) for the business valuator when giving expert testimony in the witness box, both in examination-in-chief and in cross-examination. This lengthy “checklist” was developed from both personal experience and working with eminent Canadian and American trial lawyers. I believe it may be of interest to aspiring (and even experienced) expert witnesses to obtain a view from “behind the scenes” and to see what rules and maxims have been established for the trial attorneys themselves. Just as we expert witnesses have our own “do’s and don’ts” checklist, so does the litigation lawyer cross-examining you. Crossexamination is such an important part of the trial process that entire books have been devoted to the subject. In this article, I have taken material from the writings of two Canadian and two American legal authorities: Former Supreme Court of Canada Justice John Sopinka (when he was a practicing trial lawyer) in The Trial of An Action and Ontario District Court Judge Roger Salhany in Cross-Examination: The Art of The Advocate . The American authors are Peter Brown in The Art of Questioning and the nineteenth-century trial lawyer, Francis Wellman, in his classic, The Art of Cross-Examination. My comments consist of a potpourri of the rules, or maxims, given by these renowned trial lawyers to their fellow attorneys. I hope they will provide insight as to what goes on in the mind of the cross-examiner and where he or she is “coming from,” and why. Needless to say, these rules are by no means exhaustive. Those specifically relating to criminal trials are not referred to, unless they are common to civil and commercial matters. Whenever expert evidence is involved, I have included the relevant maxims. Sopinka, in his book The Trial of An Action, gives several pages of advice (as an attorney) to trial lawyers in preparing a witness for cross-examination, and suggested: “In order to further neutralize the terror generated by the witness box the witness should be given a preview of the cross-examination. When the witness is a main witness and will be subjected to a searching cross-examination, it is often productive to plan the examination which is expected from opponent’s counsel and subject the witness to it ... . “Apart from being given a preview of the examination there are a number of ‘good pieces of advice’ about behavior from which a witness can profit ... . Don’t fence with the cross-examiner. Don’t lose your composure. ... no matter how much you dislike the cross-examiner treat him with respect. All of this will help to create a favorable impression on the tribunal.” Those of us who have already testified as a valuation expert appreciate that the foregoing instructions are those typically suggested by counsel preparing the expert for cross-examination. Sopinka notes that a witness’ evidence can be contradicted or impeached by (a) previous inconsistent statements, (b) other evidence, (c) contradiction in the witness’ own evidence or inherent improbabilities therein, or (d) attacking his or her memory, power of observation and credibility. As regards the expert (as opposed to the fact-witness), he makes the following suggestions to fellow counsel: • To cross-examine effectively, it is necessary to be schooled by an equally competent expert. • The object is to flaw him/her so that your expert is preferred. • The easiest way of discrediting the opinion is to refute a basic assumed or found fact, which may be done in cross-examination or by other evidence. • If a basic assumed fact cannot be refuted, attack the theory of the expert [presumably relying upon counsel’s own expert].
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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 | 0.059 | 0.214 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.014 | 0.047 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.020 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".