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Record W2548291894

A new team for new challenges

2013· article· en· W2548291894 on OpenAlexaboutno aff
Alessandra Faggian, J. Paul Elhorst

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmLibrary scienceWork (physics)Regional scienceSociologyOperations researchPolitical scienceEngineeringComputer sciencePsychology
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.355
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.090
GPT teacher head0.347
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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