A quarter of a century of CONCUR – Report on the 2014 and 2015 editions of the Conference on Concurrency Theory
Bibliographic record
Abstract
The international Conference on Concurrency Theory (CONCUR), which was launched in 1990 by the eponymous ESPRIT BRA project, reached an important milestone in 2015: its quarter of a century. The event was celebrated twice: first during the 25th edition of the conference, held in Rome in September 2014, and then during its 26th edition, held in Madrid in September 2015, which actually marked CONCUR’s 25th anniversary. It may be noted that both editions took place in capital cities of Mediterranean countries, witnessing the deep rooting of Concurrency Theory in Italy and its active development in Spain. This brings back to mind an old remark by Robin Milner, to the effect that Concurrency Theory, originated in Northern Europe in the late 70’s, was progressively extending its scope towards the Mediterranean, so that its epicentre was “moving South”. We give next two separate recounts of CONCUR 2014 and CONCUR 2015, with some back and forth excursions from one to the other.
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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 | 0.017 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".