Review of Understanding psychological research: An introduction to methods.
Bibliographic record
Abstract
RICHARD ST. JEAN Understanding Psychological Research: An Introduction to Methods Toronto, ON: Prentice Hall Canada, 2001, 192 pages (ISBN 0-13-027027-X, C$41.95, Softcover) Reviewed by URSULA HESS Richard St. Jean's book has the stated goal to be a brief text that presents essential concepts in a concise but interesting format. In this the author succeeds admirably. The nine short chapters and three appendices present the basic content that any method course needs to cover. The chapters are centred around lively research examples, often from the author's own work. Each chapter is followed by a brief summary and a glossary of key terms. The examples are used to introduce the methodological question and to illustrate various solutions. The first chapter presents a brief overview of fundamental concepts. Chapters 2 and 3 discuss ways to measure dependent variables using observational and selfreport techniques. The chapter on self-reports gives an excellent overview of the methodological bases of survey research; unfortunately, it remains silent on the use of self-reports in other contexts. This choice has the consequence that the important issue of the psychometric characteristics of self-report measures such as psychological tests are addressed only in passing in the introduction. Chapters 4 to 8 focus on different research plans. These chapters present research examples that are used to illustrate possible sources of confounds and biases and to propose solutions. An interesting feature is the relatively extensive treatment of archival research and unobtrusive measures presented under the heading of expost facto research. These techniques, although infrequently used by psychologists, allow St. Jean to sensitize the reader to the problems related to proper operationalization and validity of measures. Chapters 5 and 6 focus on between- and within-subjects designs. St. Jean succeeds in presenting a fairly complete description of the approaches in only about 20 pages each, and even manages to include a short but helpful introduction to the use of analysis of variance in these contexts. Chapter 7 is an equally successful primer on interaction effects. This is a definite strength of the book. Interactions are always a difficult notion to grasp for students when first confronted with the concept, and methods texts tend to ignore the issue and leave them to statistics texts, which in turn focus on how to calculate rather than to interpret interactions. St Jean's short introduction not only shows clearly how to interpret the common patterns of two-way interactions, but only provides in the process sufficient background for students to be able to grasp more complex interactive patterns. …
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How this classification was reachedexpand
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 | 0.061 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".