ADAPTIVE CAPACITY IN RESPONSE TO REVOLUTIONARY CHANGE: THE CASE OF ONTARIO’S CONSERVATION AUTHORITIES
Bibliographic record
Abstract
Adaptive Capacity in Response to Revolutionary Change: The Case of Ontario’s Conservation Authorities\nThe purpose of this research is to develop a framework of adaptive capacity based on underlying elements, as identified in the established literature, and to apply that framework to describe and explain how organizations have experienced and survived revolutionary changes. Vision, capacity building, flexibility, and monitoring and learning as a proxy indicator of resilience are determined representative of adaptive capacity and this thesis applies the resulting framework to the experiences of the Grand River and Ganaraska Region Conservation Authorities. During the 1990s, conservation authorities in Ontario experienced revolutionary changes. While adaptive capacity has been regarded as an appropriate concept to respond to revolutionary changes - changes that occur at a fast rate and high magnitude - there is an absence of effective conceptual frameworks and empirical research. This research responds to this need.\nThis research applies the framework of adaptive capacity to a document review, using NVivo qualitative-analysis software. An interview-based review confirmed findings. A methodological map guided research and facilitated discussion of which elements of adaptive capacity were applied in response to revolutionary change. Principal sources for the document review included meeting minutes and financial statements from 1988 to 2004. Meeting minutes represent an amalgamation of information created by or presented to each conservation authority’s board of directors. NVivo enabled the coding and chronological graphical representation of the occurrences of elements of adaptive capacity that were applied in relation to management functions and/orchanginginstitutionalarrangements. Interviewswithappropriaterespondents\nin\nprovided context and confirmed the elements of adaptive capacity identified in the document review.\nThis thesis provides lessons on how to investigate and implement adaptive capacity. More specifically, a review of the GRCA and GaRCA has added to the literature of adaptive capacity and to the interrelationships of its constituent parts. Conclusions of the research not only provide lessons of how adaptive capacity can be implemented, but also provides empirical examples of how those elements have been utilized by organizations that have experienced and survived revolutionary change. It is hoped that this framework and subsequent research aid organizations in the application of adaptive capacity
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".