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Record W4416779948 · doi:10.1029/2024csj000120

Situating Place‐Based, Community‐Engaged Watershed Research at Xwulqw'selu Sta'lo'

2025· article· en· W4416779948 on OpenAlexafffund
Tom Gleeson, Ella Martindale, Jennifer Shepherd, David Serrano, Kristina Disney, Tim Kulchyski, Tyrone Elliott, Eric G. Campbell

Bibliographic record

VenueCommunity Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsInstitute for Christian StudiesUniversity of TorontoCumulative Environmental Management AssociationUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSituatedWork (physics)Context (archaeology)Government (linguistics)Plan (archaeology)Representation (politics)WatershedValue (mathematics)

Abstract

fetched live from OpenAlex

Abstract Xwulqw'selu Sta'lo' is a culturally significant and salmon‐bearing river facing significant challenges, which Cowichan Tribes and the British Columbia provincial government are addressing with a first‐of‐its‐kind watershed plan. Our research is deeply situated at Xwulqw'selu Sta'lo' and is grounded in interdisciplinary academic spheres of place‐based research, water monitoring and modeling, cogovernance and systems theory. Our project is an example of developing a deliberate, robust, and responsive community science project designed to engage community, impact decision‐making, and respectfully work together in place, on the land. We describe developing and initiating our project and share a visual representation of how we structure our project as “woven statements.” The five statements give our research project team a shared understanding and motivation and help us plan and make decisions. The statements can be visualized as vertical warps interwoven with research projects, goals, and partnerships as horizontal wefts. The warps and wefts mutually support each other since weaving gains strength where warp and weft meet, connect, and overlap. Key lessons include the importance of taking responsibility for positionality, knowledge, and relationships; the value of intention setting that reflects the context and the priorities of partners and community; and that projects can flourish if structured around the good present in community.

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)0.097
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0970.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0950.004
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0000.000

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 head0.233
GPT teacher head0.465
Teacher spread0.232 · 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 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

Citations1
Published2025
Admission routes2
Has abstractyes

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