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
Abstract ‘Social return’ (SR) is a term in the Netherlands that summarises all efforts to integrate people with a mental or physical handicap in the labour market. It is an important political topic because government wants not only an inclusive society but also a decrease of expenditures on social benefits; an important topic for employers, because organisations can profile themselves as socially responsible; and a topic for applied research, finding ways and means of realising the concept. The Rotterdam University of Applied Sciences is mainly involved because of the value of SR for applied research and the development of solutions that work. Several projects have been implemented with third parties, all of them involving students, e.g. through BA graduation research. However, the research also shows that there is no large-scale adoption among entrepreneurs yet. Three problems have been identified: (1) the SR policy currently has many negative side effects; (2) entrepreneurs must recognize that the involvement of employees with a SR indication not only costs money but may also contribute to profits; (3) insufficient attention is paid to finding the proper match between possible employees and suitable jobs (possibly with an adapted working environment). However, ‘social return’ is a feasible concept and the problems may be addressed. At the same time the initial efforts on realising ‘social return’ point at the importance of organisational culture. The main aim of this paper is to show the link between organisational culture and the successful implementation of social return.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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