Monthly Archives: May 2014
Buddy Yosha, the Melvin Belli of The Midwest, meticulously outlines his examination and writes out every question and expected answer. He also uses marginal notes to signal general topics of the examination such as background, anatomy, treatment opinions, permanency, future medical expenses and treatment, etc. You get the idea. This system works well for him. Some of the other attorneys in our office have adopted it and have been successful in outlining testimony in this fashion. However, such as system has its drawbacks.
First the outline is very long. I have seen some outlines that have gone well over a 100 pages which can be cumbersome. It is basically a deposition transcript of what you hope to present. When it comes down to studying it, you are lucky to get through it two or three times in a single sitting. It can also lead to the testimony coming across scripted and stiff.
It does the have the advantage of allowing you to fully visualize the expected testimony. If you are pressed for time it can also provide a clear blueprint for the witness’s testimony which would allow a young associate or paralegal to work with the witness and know what to expect as far as the question and answer.
There is an alternative method that I use. I outline the facts I hope to obtain from the witness, in the order I hope to obtain them from the witness. I will write at the top of my outline the legal elements of the claim I expect to cover with the witness (breach of duty, proximate cause, damages, etc.) and list any exhibits by number and description , I hope to cover with the witness. I make the question up as I go. The testimony comes across spontaneous and more conversational.
From my perspective this type of outline can be reviewed multiple times because it is substantially shorter than one which has both the questions and answers. It places the emphasis on your goal, the expected answer, not the question. This forces you to listen to the witness, instead of moving on to your next question. You make up each question as you go which helps you develop the skill of forming questions on the fly. If an objection is sustained, no worry, you simply rephrase the question. It’s second nature to you.
This method forces you to develop the skill of thinking on your feet and adapting rapidly to your opponent’s objections and the Court’s rulings. Most of the time if you rephrase the question, the Court will allow you to move forward. With a scripted witness outline, I have seen attorneys freeze in their tracks when an objection is sustained because they are locked into their script and do not have the requisite skills to rephrase their question quickly. It makes them look like they are struggling and have been hurt by the legal objection. This second method of outlining a list of facts, also keeps you focused on the goal… the witness’s answer.
The only exception to this rule is when you are asking a question which requires information to be loaded into it such as for an expert witness such as a hypothetical question or when words of legal art must be included in the question, such as “Based upon a reasonable degree of medical certainty, what caused Mr. Roger’s numbness in his left arm?”
Hypothetical questions, as noted above, should be written out in advance so that no key facts are omitted. Otherwise your question could be objected to as an incomplete hypothetical or one that either misstates the record.
There is more than one way to outline your examination. Choose the method which works best for you. Both approaches have their advantages and drawbacks. Good luck!
You want to be the best you can be. You have picked up books and read the closing arguments of successful attorneys. You’ve studied their transcripts of cross-examination. You’ve memorized their tactics and one liners.
Should you imitate these masters of the courtroom, or forge your own path? Probably a little of both. It has been said that: “You might as well be yourself because everyone else has been taken.” Nothing is more credible than sincerity and you cannot sincerely be anyone but yourself.
A jury is a wise entity unto itself which is why it’s the backbone of our justice system. They’ll see through an act and don’t appreciate a slick fast talking attorney.
As Lincoln observed, “You can fool some of the people, all of the time. And, you can fool all of the people, some of the time. But you can’t fool all of the people, all of the time.” Be yourself! Lincoln was. He didn’t worry about his awkward and gangly appearance. He was great trial attorney, President and person. He is arguably the greatest leader our country has ever had. He got there being himself.
It is important to learn from the mistakes of others or you are bound to repeat them. So learn from the best, but remember in the end, only you can win or lose the case.
In my last post, I discussed readings that could help improve your knowledge and analytical skills in addressing statistical data. Below is a check list of items to consider summarized from the Manual on Scientific Evidence Third Edition, Reference Guide on Epidemiology. Here is the list:
CHECKLIST OF PROBLEMS WITH THE USE OF STATISTICAL DATA AND ANALYSIS
I. What Sources of Error Might Have Produced a False Result?
A. What Statistical Methods Exist to Evaluate the Possibility of Sampling Error?
1. False positives and statistical significance,
2. False negatives,
B. What Biases May Have Contributed to an Erroneous Association?
1. Selection bias: Selection bias refers to the error in an observed association that results from the method of selection of cases and controls (in a case-control study) or exposed and unexposed individuals (in a cohort study).
2. Information bias: Information bias is a result of inaccurate information about either the disease or the exposure status of the study participants or a result of confounding. In a case-control study, potential information bias is an important consideration because the researcher depends on information from the past to determine exposure and disease and their temporal relationship.
3. Other conceptual problems:
a. Issue or hypothesis is improperly defined: Sometimes studies are limited by flawed definitions or premises.
b. Publication bias: the tendency for medical journals to prefer studies that find an effect. If negative studies are never published, the published literature will be biased.
c. Financial bias / Conflicts of Interest: the source of funding of studies have been shown to have an effect on the outcomes of such studies by researchers.
d. Observer bias: Is bias is with the “observers” of the research (i.e., the research team) rather than the participants. In other words, observer bias occurs when the observers (or researcher team) know the goals of the study or the hypotheses and allow this knowledge to influence their observations during the study. For example, if an observer knows that the researcher hypothesized that females speak in more complex sentences, they may believe they hear females speaking that way during the study even if it’s not really true.
e. Participant bias: This occurs when participants adjust their behavior to what they think the experimenters expect. This can be a significant problem in that, if participant bias occurs, then the results of an experiment may not be entirely due to the experimenters’ manipulation of the independent variable.
f. Research bias: (also called experimenter bias): Is a process where the scientists performing the research influence the results, to portray a certain outcome.
g. Sampling bias: (also called ascertainment bias) is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others. It results in a biased sample, a non-random sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling. Examples include: Self-selection, Pre-screening, Advertising, etc.).
h. Exclusion bias: Results from exclusion of particular groups from the sample, e.g. exclusion of subjects who have recently migrated into the study area (this may occur when newcomers are not available in a register used to identify the source population). Excluding subjects who move out of the study area during follow-up is rather equivalent of dropout or non-response, a selection bias in that it rather affects the internal validity of the study.
i. Healthy user bias: when the study population is likely healthier than the general population, e.g. workers (i.e. someone in ill-health is unlikely to have a job as manual laborer).
j. Overmatching: matching for an apparent confounder that actually is a result of the exposure. The control group becomes more similar to the cases in regard to exposure than the general population.
k. Symptom-based sampling bias: The study of medical conditions begins with anecdotal reports. By nature, such reports only include those referred for diagnosis and treatment. A child not function in school is more likely to be diagnosed with dyslexia than a child who struggles but passes. A child examined for one condition is more likely to be tested for and diagnosed with other conditions, skewing comorbidity statistics. As certain diagnoses become associated with behavior problems or intellectual disability, parents try to prevent their children from being stigmatized with those diagnoses, introducing further bias. Studies carefully selected from whole populations are showing that many conditions are much more common and usually much milder than formerly believed.
C. Could a Confounding Factor Be Responsible for the Study Result? Confounding occurs when another causal factor (the co-founder) confuses the relationship between the agent of interest and outcome of interest. (e.g. Researchers must separate the relationship between gray hair and risk of death from that of old age and risk of death.) Confounding is a reality—that is, the observed association of a factor and a disease is actually the result of an association with a third, confounding factor.
1. What techniques can be used to prevent or limit confounding?
2. What techniques can be used to identify confounding factors?
3. What techniques can be used to control for confounding factors?
II. General Causation: Is an Exposure a Cause of the Disease?
A. Is There a Temporal Relationship?
B. How Strong Is the Association Between the Exposure and Disease?
C. Is There a Dose–Response Relationship?
D. Have the Results Been Replicated?
E. Is the Association Biologically Plausible (Consistent with Existing Knowledge)?
F. Have Alternative Explanations Been Considered?
G. What Is the Effect of Ceasing Exposure?
H. Does the Association Exhibit Specificity?
I. Are the Findings Consistent with Other Relevant Knowledge?
I would urge you to check this free and comprehensive source of information on scientific evidence.