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Record W4415689075 · doi:10.1007/s10040-025-02955-7

Hydrogeology, European colonialism, local communities and First Peoples: moving beyond business as usual

2025· article· en· W4415689075 on OpenAlexaff
Sarah A. Bourke, Matías Taucare, Élise Devoie, Clint J. Hansen, Stephanie Wright, Margaret Shanafield, Viviana Ré, Aurora Kagawa‐Viviani, Allanah Kenny, Mandiaye Diene, David K. Kreamer, Brendan Mulligan, Theo S. Sarris, Mark Cuthbert, Kelly-Jane Wallis, Bradley Moggridge

Bibliographic record

VenueHydrogeology Journal · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWater management and technologies
Canadian institutionsYukon Department of Environment
FundersUniversity of Western Australia
KeywordsHydrogeologyColonialismResource (disambiguation)Process (computing)Through-the-lens meteringGroundwater

Abstract

fetched live from OpenAlex

Abstract European colonialism altered the connections between First Peoples, local communities, and groundwater systems across the world. In many countries, the practice of hydrogeology remains intertwined with the economic agendas of colonial settler communities, making colonialism a useful lens through which to consider our work. This paper briefly summarizes connections between First Peoples, local communities and groundwater, as well as the role of groundwater as a resource in the process of European colonization. The key contemporary legacies of colonization pertaining to groundwater resource utilization and management are outlined, and established human rights that relate to the practice of hydrogeology are highlighted. The paper concludes with a call for more meaningful relationships between hydrogeologists and local communities, a broader practice of hydrogeology that respects and integrates traditional knowledge and community perspectives so that we can walk together into a better future.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.024
Scholarly communication0.0090.006
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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.

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

Citations5
Published2025
Admission routes1
Has abstractyes

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