Feelgood Management in German SMEs and its Impacts on Employees’ Health, Satisfaction and Performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Feelgood Management is an emerging concept first applied in the German start-up scene in 2012. The approach is gaining popularity, even though the measurement is difficult and academic research is scarce. Accordingly, this study aims to close this research gap by answering the research question about the impact of Feelgood Management in German SMEs, especially on the employees’ heath, satisfaction and performance willingness. Our findings show that Feelgood Management is just emerging and faces several challenges, related to the ambiguous term that implies ridicule, the lack of standardization that is allowing various interpretations and opposition towards novelty. Despite being limited, due to the risk of bias and subjectivity that is natural for qualitative data collection along with the uni-dimensional perspective of solely Feelgood Managers, this study produces a valuable model of the influences on Feelgood Management and its impact on employee health, satisfaction and performance willingness.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it