Three decades investigating humor and laughter: An interview with Professor Rod Martin
Bibliographic record
Abstract
Since the start of the 21st century, the investigation of various psychological aspects of humor and laughter has become an increasingly prominent topic of research. This growth can be attributed, in no small part, to the pioneering and creative work on humor and laughter conducted by Professor Rod Martin. Dr. Martin's research interests in humor and laughter began in the early 1980s and continued throughout his 32 year long career as a professor of clinical psychology at the University of Western Ontario. During this time, Dr. Martin published numerous scholarly articles, chapters, and books on psychological aspects of humor and laughter. Professor Martin has just retired in July 2016, and in the present interview he recounts a number of research highlights of his illustrious career. Dr. Martin's earliest influential work, conducted while he was still in graduate school, stemmed from an individual difference perspective that focused on the beneficial effects of sense of humor on psychological well-being. This research focus remained evident in many of Professor Martin's subsequent investigations, but became increasingly refined as he developed several measures of different components of sense of humor, including both adaptive and maladaptive humor styles. In this interview, Dr. Martin describes the conceptualization, development and use of the Humor Styles Questionnaire, along with suggestions for future research and development. In doing so, he also discusses the three main components of humor (i.e., cognitive, emotional and interpersonal), as well as the distinctions and similarities between humor and laughter. Further highlights of this interview include Professor Martin's comments on such diverse issues as the genetic versus environmental loadings for sense of humor, the multifaceted nature of the construct of humor, and the possible limitations of teaching individuals to use humor in a beneficial manner to cope with stress and enhance their social and interpersonal relationships.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.023 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".