Mapping the contours of contemporary positive psychology.
Bibliographic record
Abstract
This paper seeks to quantify scholarly interest in the rapidly emerging field of Positive Psychology (PP) and to empirically map the contours of the discipline using six different methodologies. Results document extraordinary growth in the last decade and confirm that scholars in this area have devoted the lion's share of their attention to two of the three 'Pillars' of PP as proposed by SeUgman and Csikszentmihalyi (2000): (1) the study of positive subjective experience and (2) positive personal traits. While interest in positive institutions has been somewhat sparse, there has been increased concern with the topics of 'resilience' and eudaimonia (broadly defined). The latter developments help to dispel the myth that PP is an elite endeavour solely concerned with Pollyanna-style 'happiology' in people who find themselves in idyllic circumstances. Hopefully the results of our content analysis of the field will encourage instructors who teach PP to provide their students with a well-balanced curriculum, one that accurately reflects the heterogeneity of the field, and one that mirrors recent scholarly trends. Keywords: definition, positive psychology, review, domains, temporal trends, specializations As Noted by Yen (2010), the past 10 years, there has been a literal explosion of work within the new subdiscipline of positive psychology. Commanding record enrollment rates in undergraduate psychology courses across North America and around the world and attracting a considerable amount of media attention, positive psychology has become positively faddish. It is Harvard's most popular course, having recently supplanted introductory economics. . . . Within the academy, the field has rapidly established itself through a large and growing body of research data, journals, books, articles and special issues, international associations and conferences, funding, dedicated research centers, and courses and graduate programs. (p. 67) While a number of authors have noted that increased attention is being given to Positive Psychology (PP), pronouncements of a boom have rarely been substantiated by empirical research that has approached the question using a quantitative methodology. In the current article, we document the growth of scholarly interest in PP by performing a year-by-year count of citations contained in PsycINFO. At the same time, in an effort to contribute to 'boundary work,' we also empirically map the contours of the field using six different methodologies. To briefly preview our findings, we were able to confirm anecdotal observations (e.g., Yen, 2010) suggesting PP has experienced extraordinary growth in the past decade. Our empirical efforts to demarcate PP' s self-narration yielded a heterogeneous picture. Content analyses of subdomains of concern to PP suggest a complex identity, one that is incongruent with the popular cultural stereotype that depicts PP as an elite endeavour concerned solely with grinning yellow smiley faces and Pollyanna-style positive thinking. We conclude our paper by encouraging instructors who teach PP to make use of the current results so as to provide students with a well-balanced and comprehensive curriculum, one that accurately reflects the empirically determined breadth and scope of the field. What Is the Evidence for a Boom? Wong (2011) agrees with Yen (2010) in suggesting PP has rapidly become a 'hot' topic in academic circles and in the popular culture. While anecdotal accounts touting the PP boom are plentiful, research is lacking that documents changes in the extent of interest in the academy over time. There is also a dearth of empirical evidence to quantify how much scholarly attention has been given to specific topic areas and whether interest is burgeoning equally in these emerging subdomains of inquiry. Thus, we do not know whether the boom that has ostensibly occurred since the year 2000 is generalised or localised to a few constructs/processes. …
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".