Burnout: 35 years of research and practice
Bibliographic record
Abstract
Purpose The purpose of this paper is to focus on the career of the burnout concept itself, rather than reviewing research findings on burnout. Design/methodology/approach The paper presents an overview of the concept of burnout. Findings The roots of the burnout concept seem to be embedded within broad social, economic, and cultural developments that took place in the last quarter of the past century and signify the rapid and profound transformation from an industrial society into a service economy. This social transformation goes along with psychological pressures that may translate into burnout. After the turn of the century, burnout is increasingly considered as an erosion of a positive psychological state. Although burnout seems to be a global phenomenon, the meaning of the concept differs between countries. For instance, in some countries burnout is used as a medical diagnosis, whereas in other countries it is a non‐medical, socially accepted label that carries a minimum stigma in terms of a psychiatric diagnosis. Originality/value The paper documents that the exact meaning of the concept of burnout varies with its context and the intentions of those using the term.
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 | 0.040 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".