“Faster Alone, Further Together”: Reflections on INKE’s Year Six
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
Background: This article examines Implementing New Knowledge Environments’ (INKE) experiences as a mature, large-scale collaboration working with academic and non-academic partners and provides some insight into best practices. It looks at the sixth year of funded research.Analysis: The study uses semi-structured interviews with questions focused on the nature of collaboration with selected members of the INKE research team. Data analysis employs a grounded theory approach.Conclusion and implication: The interviewees found the experience of collaborating within INKE to be positive with some ongoing challenges. The team is winding down as it moves into the final year of funded research. This suggests an arc of collaboration, with intensity of collaboration building from the first year to the most intensive time in the middle years and then winding down in the last years of grant funding. This article contributes to those lessons about collaboration by exploring the lived experience of a long-term, large-scale research project.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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