Planning ahead: Toward a critical, environmental, just, and action-oriented planning theory, practice, and journal
Bibliographic record
Abstract
This essay contributes to the 10th Anniversary Special Issue of plaNext – Next Generation Planning by offering reflections and ideas for inspiring a renewed roadmap in planning theory and practice that more systematically incorporates tools and contents from emerging critical disciplines. It emphasizes the crucial contributions that young researchers and planners can make through their work, as well as the potential of a journal led by early-career scholars—such as plaNext—to shape the field. The paper introduces the contemporary challenges facing planners within the context of the current global polycrisis, i.e., crisis of the ecosystem, society, democracy, and knowledge. Such a polycrisis will be linked to the urgent need for renewal in the field and a rethinking of how planning scholars and practitioners contribute to and engage with societal transformation and existing inequities and injustices. Drawing on emerging critical disciplines—including critical ecofeminism, critical disability studies, critical environmental justice, critical heritage studies and critical eco-museology, multispecies justice and critical animal studies, critical food studies, and urban political ecology—the essay explores how these perspectives have brought an ecosystemic understanding of the axes of power that drive inequality and injustice. It examines the extent to which these perspectives have already been incorporated into planning studies, the added value of integrating their critical tools, and the potential for planners and policymakers to engage in spatial and practical experimentation with these provocative concepts. Finally, the essay outlines some ideas for what a journal like plaNext could do for providing a space for innovative theoretical developments while supporting action- and justice-oriented work—both of which are increasingly crucial in today’s global context.
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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.076 |
| Scholarly communication | 0.028 | 0.028 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".