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Record W4386932430 · doi:10.1177/10323732231196939

A multi-period analysis of a water management arena in the Italian Alps, circa 1951–2007: The territorialisation of environmental concerns

2023· article· en· W4386932430 on OpenAlexaff
Laura Maran, Thomas Schneider, Michele Andreaus

Bibliographic record

VenueAccounting History · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsToronto Metropolitan University
FundersUniversidad Pública de NavarraUniversity of Portsmouth
KeywordsHydropowerSustainabilityMillerEnvironmental historyStakeholderWater qualityVisibilityEnvironmental planningEnvironmental resource managementPolitical scienceEnvironmental protectionEnvironmental ethicsGeographyHistoryEconomic historyLawEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Water exploitation is at the centre of current social and environmental sustainability discourses, one form of which is hydropower. Intense damming of rivers and natural basins occurred in nineteenth and twentieth century Europe (and elsewhere). Following Miller and Power's concept of territorialisation and Foucault's notion of visibility, this study sheds light on the water management arena, read through changes in stakeholder objectives and accountabilities. Its focus is on the ‘accounts’ of environmental concerns, from post WWII to the new millennium. The analysis focuses on the case of the Santa Giustina dam in Northern Italy, using archival and oral-history approaches. It is shown how an increasing visibility of environmental concerns translated into a higher degree of ‘territorialisation’ through their itemisation in water quality and quantity parameters. This historical evolution informs policy makers, managers and society in general, about how to address profits and environmental issues regarding current water exploitation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.249
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations6
Published2023
Admission routes1
Has abstractyes

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