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Record W2975552234 · doi:10.3390/w11102046

Everyday Practices, Everyday Water: From Foucault to Rivera-Cusicanqui (with a Few Stops in between)

2019· article· en· W2975552234 on OpenAlexaff
Kathryn Furlong, Denisse Roca‐Servat, Tatiana Acevedo-Guerrero, María Botero-Mesa

Bibliographic record

VenueWater · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSociologyScholarshipNeoliberalism (international relations)PoliticsEpistemologySection (typography)PrecarityPragmatismPerspective (graphical)AestheticsSocial scienceGender studiesPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

In this article, we explore elements of the literature on practices and the everyday to provide reference points for water researchers. We cast a wide net in recognition of the complex and multifaceted nature of human relationships to water that cannot be reduced to a single perspective. The article begins with the work of prominent French theorists including Foucault, Lefebvre, Bourdieu and de Certeau. Each grapples with the interrelationship between wider socio-political processes and practice in different ways. This leads us to pragmatism and non-representational theory in the second section, which argue that to understand socio-political processes, one must begin from practices. In the third section, we engage with work on practices in conditions of instability and precarity, which are widespread under contemporary conditions of post-colonial neoliberalism, and the role of “care” in mitigating their effects. In section four, we discuss the scholarship and practice of Silvia Rivera-Cusicanqui, who explores and extends many of the approaches elaborated above. The article concludes with a reflection on what this means for engaging with the multiple realities and ways of living with water.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.013
GPT teacher head0.275
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations10
Published2019
Admission routes1
Has abstractyes

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