Territorial Competitiveness for the Interests of Publics
Bibliographic record
Abstract
Competitiveness refers to a territory successfully satisfying its aims and objectives. In both research and practice, aims and objectives are usually specified in terms of compatibility with market success – e.g. performance in international trade - and/or the success of hierarchies – e.g. performance of large corporations. We suggest a different paradigm, focused on compatibility with the interests of publics. Achieving this would require forums where people could freely inquire about the territory. They could then recognise their concerns about choice of the territory’s aims and objectives, and might identify when they share concerns, i.e. when they constitute a public. The forums would enable people to learn and experience, observe, discuss, share understanding and ideas, express their voice, and listen to others. Despite university governance and epistemic governance tending to crowd-out space for activities centred on publics, one way that researchers can help to create forums is by cooperating with citizens, community groups, policy-makers, and diaspora. Together, they might reframe the nature and purpose of territorial competitiveness, making it for the interests of publics.
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.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".