MétaCan
Menu
Back to cohort
Record W7027360340

Collaborative management: A framework for source water protection in the Maitland Valley watershed, Ontario

2006· dissertation· en· W7027360340 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2006
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipWatershedStakeholderWater sourceWatershed managementPlan (archaeology)Conceptual frameworkSocial network analysisConceptual model
DOInot available

Abstract

fetched live from OpenAlex

The Province of Ontario has introduced the 'Clean Water Act' as a means to protect sources of drinking water and implement the last of the Walkterton Inquiry recommendations. The 'Clean Water Act' is to be watershed-based with plan development facilitated by conservation authorities across the province. This thesis is a case study of the Maitland Valley watershed and investigates the potential for collaborative management as a framework for source water protection. Stakeholder analysis methodology is used to examine the social network of the Maitland Valley watershed for source water protection, and analyze the nature of the social network with regard to relationships and communication. Social network maps were generated to conceptualize the presence of relationships, both supportive and conflictive, among the stakeholders groups. Patterns of interest, communication and learning, collaboration and partnership are detailed. A conceptual framework that proposes guiding principles for collaboration was derived from the literature. Based on the findings this thesis then reflects on the usefulness of these principles as a tool for the development of collaborative management. Suggestions for using a collaborative management framework for source water protection are then put forward.

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)0.000
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 score0.355
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.195
Teacher spread0.182 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)Same topicOrganizational Learning and LeadershipFrench-language works237,207