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
Purpose This study aims to investigate how an organic cotton production network learns to maintain its hybrid network and its sustainability in the face of internal and external pressures. Design/methodology/approach A qualitative case study was conducted in Justa Trama, a Brazilian‐based organic cotton production network formed by six members with different roles and organisational logics. Findings The study contributes to the literature on hybrid organisations by suggesting that in the case of networks, a compromise strategy is required at the internal level and a manipulation strategy is required at the external level. The network has to learn how to engineer a compromise among internal members and to enforce change among external institutions to maintain its sustainability. Social implications The study was performed in Brazil, a country with serious social and environmental problems. The study thus informs managers of social economy organisations on how to deal with internal and external pressures to maintain their organisation's sustainability as well as policy makers on the importance of these alternative organisations and the importance of specific legislation to stimulate this type of initiative. Originality/value The body of research on how hybrid organisations learn to deal with the mutual influence of internal organisational responses and changes in external institutions is limited. Furthermore, this mutual influence has rarely been studied in the context of networks, in which multiple members have to work together to achieve organisational and network‐level objectives as well as to respond to institutional pressures.
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) | 0.000 | 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) | 0.001 | 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