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Record W2791859321 · doi:10.4095/306494

Pinning down demand for groundwater geoscience: from narratives to numbers

2018· report· en· W2791859321 on OpenAlexaffabout
S V Z de Jong, H A J Russell, H DeGeer, Helen Burke, L Strychar

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGroundwaterNarrativeEarth scienceEnvironmental scienceGeologyGeotechnical engineeringArt

Abstract

fetched live from OpenAlex

Indigenous people require fit-for-purpose groundwater-surface water data to help First Nations strengthen the federal legislation governing the requirements of safe drinking water for First Nations On-Reserve. Prior to the 2009-2011 National Assessment of First Nations Water and Wastewater Systems, there was no nationally representative data on First Nations On Reserve groundwater geoscience. Currently, this rudimentary baseline report suggests that 158 water systems serve 115 Ontario First Nations. Within this, there are 94 surface water systems, 39 groundwater systems and 13 groundwater-under-the-direct-influence-of-surface-water systems. Ironically, the application of Province of Ontario regulations (such as the Provincial Policy Statement) to Reserve lands are viewed as best practice. Federal government water system policy and practice is not regulated and enforced. Rather, it is also viewed as best practice. This fragmented jurisdiction issue has direct implications to First Nations (FN) On-Reserve who rely on informal water management systems. Against this backdrop, FN must compete for special project, private or charitable funding sources to generate the science required to protect their drinking water sources. This study has a twofold intent: a) determine how publically funded geoscience providers could meet the groundwater geoscience information needs of 27 First Nations (FN) in Ontario Source Protection Regions; and, b) work with FN stakeholders to refine direction for future funding decisions that may protect raw water sources from threats to water and wastewater systems. Methods used included secondary data analysis, interviews with stakeholders (email, telephone and face to face) and focus groups, case study of water security service delivery review, and review of academic articles and primary documents (FN task forces, workshop and symposium reports). Factors examined included: Five different schools of thought around Ontario source water protection (SWP) planning; the competition and concentration trends within the Southern Ontario source water protection plan (SWP) industry. Progressively deepening communication gaps between well funded geoscience providers and Ontario First Nations South of 60 (who have pressing SWP geoscience information needs that are unique to First Nations On-Reserve rather than urban Canadians. Currently - 74 First Nations' On-Reserve live with boil advisory alert, and 7 First Nations live with do not drink advisories). Unfortunately First Nations On-Reserve within Ontario Source Protection Regions have not been working closely with geoscience providers (i.e. 36 Regional Conservation Authorities mandated to develop watershed SWP in 19 Source Protection Regions). This preliminary report provides some direction for future groundwater/source water research, education and outreach with Indigenous people in Canada. According to our project First Nations' On-Reserve Source Water Protection in Ontario Source Protection Regions there is an emerging need for geoscientists to: a) work with Indigenous technical services; b) to speak and understand an Indigenous language; and c) to grow the Indigenous capacity to interpret and apply aquifer-groundwater-surface water data. Encouraging Indigenous people's participation in groundwater geoscience is an opportunity that federal, provincial and municipal institutions should grasp. Building such efforts may provide 27 First Nations in Ontario Source Protection Regions with future On-Reserve-context-specific aquifer-groundwater-surface water data integration and risk analysis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.334
Teacher spread0.292 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2018
Admission routes2
Has abstractyes

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