Portrait of a scientist: in conversation with Hubert Hermans, founder of Dialogical Self Theory
Bibliographic record
Abstract
This interview-based article about Hubert Hermans, founder of The Dialogical Self Theory (DST), was intended to determine the founder's personal relationship to the construction and development of his theory and to provide a portrait of the engaged scientist and vulnerable researcher at work. DST lends itself to interdisciplinary research and practice, and is used in diverse fields and contexts (e.g. psychotherapy; bereavement scholarship; higher education). However, little has been written about the founder of the theory. I embarked on this project to illuminate the researcher and theorist as an individual who taps into personal material for practical and conceptual learning, and to honour Hermans's contribution to the field of psychology, in the spirit of a Festschrift.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.034 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.033 |
| 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".