Interview: Regeneration in Lincoln: An interview with Tom Blount and Laura Dunne from Lincolnshire Co-operative Society
Bibliographic record
Abstract
The UKSCS conference 2023 was supported by Lincolnshire Co-operative Society and included guided tours of the Lincoln Science and Innovation Park, and The Cornhill Quarter, developments led by Lincolnshire Co-op in partnership with key organisations across the city of Lincoln, UK. Mike Wistow interviewed Tom Blount and Laura Dunne to find out more about these developments, the Society’s unique approach to regeneration, and their reflections on the advantages of being in co‑operation for over 160 years. Tom Blount is the Director of Lincoln Science and Innovation Park. Laura Dunne is Head of Marketing and Membership for Lincolnshire Co-op. Much of the conversational style of the interview has been deliberately captured in this article to give a sense of the excitement and passion that Laura and Tom have for their work, the Society, and Lincoln.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.010 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".