Contentious ontologies of a neglected water infrastructure: a chronotopic analysis of the Padua-Venice waterway controversy
Bibliographic record
Abstract
In this article, I examine the contentious dynamics surrounding the ontologies of the Padua-Venice waterway, focusing on the role of the legitimization of hydraulic expertise at the intersection of social mobilizations and institutional politics. A key sociological issue is the legibility of environmental conflicts in the context of institutional opacity, which obscures public understanding and relegates these issues to zones of non-knowledge. In this regard, I propose to expand Jack’s (2022) chronotopic expertise by considering ignorance as a part of the framework. The aim is to combine the ontological politics of water infrastructural transformation with the enactment of both scientific expertise and strategic ignorance while grounding them in a spatiotemporal configuration. Through an analysis of 20 years of local press coverage, I trace the evolution of the controversy, showing how the contested legitimacy of hydraulic expertise shifts over time, from being initially overlooked to becoming central to the debate. The controversy has been thus discussed through the relation between three hegemonic ontologies and relatives chronotopes: the waterway as a negative infrastructure and the absence chronotope; a multifunctional ontology and the metis chronotope; a flood diversion canal ontology and the hydrocratic chronotope.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".