The ‘peri-urban turn’: A systems thinking approach for a paradigm shift in reconceptualising urban-rural futures in the global South
Bibliographic record
Abstract
With the rapid pace of urbanization, urban sprawl has become a prevalent phenomenon, particularly in the global South, leading to the emergence of peri-urban spaces where rural-urban interfaces occur. These peri-urban areas exhibit dynamic and continuous interactions among social, economic, and environmental systems, offering valuable insights for fostering resilient futures. However, this aspect remains largely unexplored in current research due to a lack of innovative methodological approaches that effectively capture the complementarities, potentialities, and contestations inherent in the dynamics of peri-urban areas. We contend that peri-urbanisation needs to be reconceptualized as an alternative socio-spatial framework that extends the predominantly Eurocentric discourse on counterurbanisation, making it more inclusive of the emerging urban-rural transformations in the global South. By doing so, we can better understand and address the complex dynamics and challenges associated with peri-urban areas and develop strategies to foster resilience in these contexts.
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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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.054 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".