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Record W4286823253 · doi:10.1080/10705422.2022.2103864

Crisis and opportunity: the impacts of COVID-19 on water advocacy in Ontario, Canada

2022· article· en· W4286823253 on OpenAlexafffundabout
Robert Case, Allison Eady

Bibliographic record

VenueJournal of Community Practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceEconomic growthBusinessPublic administrationEnvironmental planningGeographyMedicineVirologyEconomicsOutbreak

Abstract

fetched live from OpenAlex

This article provides results from interviews and a focus group conducted at two different points in time in the first year of the COVID-19 pandemic, which explored impacts of the pandemic and adaptation among water advocacy organizations in southern Ontario, Canada. Our findings show that despite the destabilizing and sometimes devastating impact of COVID-19 on grassroots organizations and their programs, by disrupting business as usual the pandemic also created the conditions for experimentation, innovation, the establishment of new capacities and strategic foci. In this paper, we share descriptive narratives from water activists in our geographic area about how they adapted and innovated their work despite the challenges of the pandemic. Our findings illustrate and add nuance to themes emerging in the literature about the impacts of the pandemic on environmental advocacy groups and other nonprofit organizations, and generate new themes for further exploration.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0390.014
Scholarly communication0.0060.002
Open science0.0020.008
Research integrity0.0020.003
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 head0.061
GPT teacher head0.350
Teacher spread0.289 · 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 designObservational
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
Published2022
Admission routes3
Has abstractyes

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