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Record W4416588248 · doi:10.24306/plnxt/114

Editorial: plaNext and planning in transition (2015–2025)

2025· article· W4416588248 on OpenAlexaff
Sıla Ceren Varış Husar, Elisa Privitera

Bibliographic record

VenueplaNext - Next Generation Planning · 2025
Typearticle
Language
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsEquity (law)Plan (archaeology)Spatial planningTransition (genetics)Field (mathematics)Emerging technologies

Abstract

fetched live from OpenAlex

When plaNext first emerged in 2015, it was born out of a decision that the field of spatial planning needed a dedicated platform for emerging scholars who would highlight new voices. Ten years later, the world we plan for has shifted significantly, and so has our journal. The purpose of this special issue “plaNext in Transition 2015–2025” is to reflect on the journal’s evolution over the past decade and to envision its future trajectory for the next ten years. It marks a moment of reflection and reimagination. Over the past decade, plaNext has accompanied and often anticipated momentous changes: the climate emergency transitioning from future threat to present crisis, new movements for social justice and spatial equity gaining visibility, digitalization and AI altering how we imagine urban futures, and an increasingly interconnected yet still fractured global planning discourse. We thought that it would be interesting to see how plaNext has evolved over the last decade, and to reflect on the next decade for the journal, especially as the name of the journal implies to “plan” what is coming “next” as in “next generation of planners and planning as a discipline”. This special issue brings together contributions on both editorial developments and future directions, as well as on current planning debates, challenges, and emerging trends.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.317
Teacher spread0.264 · 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
GenreEmpirical

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
Published2025
Admission routes1
Has abstractyes

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