Bibliographic record
Abstract
During the ERSA conference in Bratislava last August the RSAI Council appointed me as Editor in Chief of the Papers in Regional Science for the next three years. At the NARSC Conference in Ottawa at the beginning of November the new editorial team was chosen: Alessandra Faggian, Ohio State University, representing RSAmericas, Paul Elhorst, University of Groningen, representing ERSA, Takatoshi Tabuchi, University of Tokyo and Yoshi Hayashi, Nagoya University, representing PRSCO. The representatives of PRSCO have already served for one term, and accepted to continue for another three year term, guaranteeing continuity with the previous team. In addition, Eduardo Haddad, Sao Paulo University, was appointed as Book Review Editor. The new team has high potential. It is composed of relatively young people, willing to serve the journal with enthusiasm, ideas and time to dedicate to this work; the scholars appointed cover a wide spectrum of disciplines, from regional and urban economics, to transport and environmental economics, spatial econometrics, economic geography. Moreover, they are characterized by different and complementary approaches to regional science, from qualitative to modelling methods and tools; from conceptual to analytical theoretical frameworks. These features allow us to say that Papers in Regional Science will be able to handle all different kinds of regional science papers, as in the past. We inherit a journal well positioned in the international scientific world thanks to the work of the previous editorial teams. The impact factor of Papers in Regional Science, as well as the number of submissions and the number of papers downloaded, has steadily grown over the past six years. The number of pages per issue has also increased, allowing the time between on line and printed version publication to be shortened. On behalf of all the RSAI community, I would like to express my gratitude to Jouke van Dijk, previous Editor in Chief, and to all the members of the previous editorial team, for these invaluable achievements. This wealthy situation is an advantage for the new team. We can go on following the trajectories established by the previous team, and thanks to the exploitation of the good reputation that the journal has achieved, I am sure we will achieve good results. Our efforts will also be directed at strengthening some aspects of the journal, which call for specific attention, such as: (i) increasing the number of submission from authors based in the Pacific area where the journal’s presence is more limited (especially if compared to Europe); (ii) solidifying and reinforcing the journal’s position in North and South America. This would also require a clear analysis of the competitors in this area, so as to put in place a truly winning strategy; (iii) balancing the presence of papers in the different fields of regional science, which include not only economics – a traditional strong area of the journal – but also other disciplines. Some strategies can be foreseen to achieve these goals. For example, the allocation of special issues to highly qualified scientists in the Pacific and American areas or in fields other than economics; engage highly-qualified scientists from China and India in submitting papers and advertising the journal to other qualified scientists in the area. However, in a world of fierce competition as the one of international journals, the best strategy is to clearly specify the editorial nature of the journal. In particular, I have the ambition doi:10.1111/pirs.12012
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 | 0.029 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.039 | 0.040 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.017 | 0.031 |
| Insufficient payload (model declined to judge) | 0.100 | 0.066 |
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".