Riverfront as a re-territorialising arena of urban governance: Territorialisation and folding of the Xindian River in Taipei metropolis
Bibliographic record
Abstract
This paper foregrounds the riverfront as a re-territorialising arena of urban governance. Through a long-term study of the Xindian River in Taipei metropolis, Taiwan, we illustrate how the riverfront can be the key locus where the expansion of the urban frontier is manifested through and intertwines with the transformation of nature. While first interwoven with everyday activities of subsistence, Xindian River was gradually turned into the periphery of the city and then green space for recreation, a process actualised through infrastructure aimed at flood control and waste treatment as well as other informal activities that challenge such measures. We propose that ‘territorialisation’ and ‘folding’ are notions that can grasp asymmetrical relations embedded in the physical landscape. We argue that a riverfront landscape composed by territorialisation and heterogeneous folding reveals that the emergence of a negotiable state–society relationship is pivotal in the production of the urban riverfront of Taipei.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".