Knowledge‐Intensive Business Services and Regional Development: Strategic Importance of
Bibliographic record
Abstract
Knowledge‐intensive business services (KIBS) have emerged as a key sector in the knowledge economy, both as conveyors of expertise and as vectors of information exchange playing an important – but sometimes underappreciated – role in innovation dynamics. They can contribute to the economy directly by exporting, and indirectly by assisting other economic actors in their export‐oriented business activities. A key question has been, and remains, the extent to which local economies require KIBS in their midst or can benefit from KIBS imported from other regions. Attracting and retaining KIBS locally may seem attractive to regions seeking to diversify their economies and enhance their local innovation systems, but it is far from certain that such a strategy is feasible or likely to succeed: local establishments may benefit more from interacting with specialized KIBS in other regions (often cities), and new communications technologies, combined with intermittent face‐to‐face meetings, are making this increasingly possible.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".