Farm-level factors influencing farmers satisfaction with their work.
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
Well-being of farm workers is necessary in order to foster farming sustainability. We contribute with the research on well-being, exploring on what extent farm-level features influence farmers satisfaction with their work and with their quality of life, using a data sample of 1099 farms in nine European countries. Results suggest that satisfaction with the farm work has a significant and large influence on the satisfaction with the quality of life. Farm-level aspects such as working time, age of assets, financial situation of the farm and social engagement significantly influence farmers satisfaction with farming but their joint effect explains less than a quarter of it. Acknowledgement : We acknowledge FLINT project. This work was funded by the EU Seventh Framework Programme grant number 613800. The opinions expressed in this paper are not necessarily those of the EU. This article is based on the deliverable D.5.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 it