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Record W2068847973 · doi:10.1080/07011784.2014.942576

Exploring the behavioural attributes, strategies and contextual knowledge of champions of change in the Canadian water sector

2014· article· en· W2068847973 on OpenAlexaffvenueabout
Danica Straith, Jan Adamowski, Kate Reilly

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsChampionPublic relationsContext (archaeology)MandateSustainabilityPolitical scienceBusinessSociology

Abstract

fetched live from OpenAlex

Sustainable water resource management (WRM) is failing to be fully implemented in Canada due to, among other things, cultural and structural inhibiting factors. There is a need for water professionals to develop their understanding of the ways in which cultural and structural barriers within prominent water resource management institutions can be broken down and/or navigated so that climate change and sustainability challenges can be more appropriately addressed. This study explored, for the first time in Canada, champion leadership approaches by interviewing champions in the Canadian water sector, with a focus on behavioural attributes, strategies and contextual factors. The findings revealed the significance of both formal and informal relationships, passion in communication, respectful and humble networking and work relations alongside necessary risk taking as key behavioural strategies for Canadian water champions. It also exposed the need to understand contextual realities of mandate gaps, control and secrecy at the federal level versus the more open and responsive culture at the municipal level. While the context can inhibit change, it does not necessarily inhibit it if the champion is well equipped to understand the institution and the strategies that can influence it. Such strategies include the creation of windows of opportunities and the use of media such as journalists, for risk-taking change efforts that do not have to be socially and professionally threatening. Water professionals who have a better understanding of the champion experience in Canada may be in a better position to contribute to a more effective implementation of sustainable WRM in Canada.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.118
GPT teacher head0.239
Teacher spread0.121 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations36
Published2014
Admission routes3
Has abstractyes

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