Bibliographic record
Abstract
Increasingly, information systems development has been recognized as a sociotechnical endeavor. We have seen calls in professional literature and at MIS conferences that IT workers must develop soft skills and emotional literacy and that they must learn to “grow their whole selves”, to quote Extreme Programming initiator, Kent Beck. Many stories abound of system development efforts where the system was built right, but it was not the right system; that is, it did not satisfy the real needs of the users. As well, we see increasing reports of burnout among IT professionals, as the business and organizational environments look for an increasingly impactful role from newly developed systems. To quote Edward Yourdon (2002), “Burnout is still a topic that most senior managers would rather not confront, but it has become so prevalent and severe that some IT organizations have become almost completely dysfunctional” (cover page). The IT profession, no doubt, has been undergoing continual change in its orientation, methodologies, and technological tool sets. To deal with this constant change and increased expectations from IT, it has been proposed that the profession adopt an interdisciplinary, holistic approach to professional development, similar to that of an Olympic athlete who would consult the areas of physiology, psychology, nutrition, kinesiology, and so forth to enable optimum performance. A powerful ally in the IT professional’s quest for inner balance and resilience is multidimensional psychological awareness. IT work is done mostly with one’s mind, one’s psyche, and thus, a deeper awareness and understanding of one’s own inner psychological dynamisms and those of one’s co-workers is advisable. System developers can release previously pent-up, unavailable psychic energies for a more effective and less stressful work effort. Possible areas of psychological functioning that would warrant specific, concerted attention from the IT profession at this point in its evolution are personality typing systems, cognitive, creativity, and learning styles and also the reality of the “deepest inner self” (core or spirit). Until now, focus on psychological factors in IT has been growing, albeit rather slowly. Groups of IT workers may have been introduced to a psychological perspective at a one-day seminar with no extensive, planned follow-up. A few organizations have taken their interests further and involved IT team members in exercises and assessments of the effect of their newly developed interests on their work performance and satisfaction. However, it may indeed be true that now the time has come for a concentrated effort in the IT profession to involve psychological factors in a more widespread, concerted, and thorough manner. The recent book, Managing Psychological Factors in Information Systems Work: An Orientation to Emotional Intelligence by Kaluzniacky (2004), provides a vision for such a possibility and issues a call to action. Psychological aspects promoted are the Myers-Briggs (MBTI) and Enneagram personality types; Kirton’s Adaptor/Innovator cognitive styles, creativity styles as measured, for example, by the Creative Styles Inventory; four learning styles as defined by Kolb (1984); the deepest inner self as outlined by the PRH (1997); and Hoffman (1988) personal growth programs, and promoted by contemporary authors such as Borysenko (1990), Bedrij (1977), Dyer (1995), McGraw (2001), and Weizenbaum (1976). The book promotes professional acceptance and application individually and collectively and suggests specific areas for both academic research and development of materials (e.g., a full-scale methodology for psychological factors in IT) to facilitate such an acceptance within the IT profession.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".