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Record W2336376044 · doi:10.14288/1.0167265

Resilient governance : the politics of nature protection in New Zealand, Norway and Canada's British Columbia

2014· article· en· W2336376044 on OpenAlexaboutno aff
Elena Feditchkina Tracy

Bibliographic record

VenueOpen Collections · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsCorporate governancePolitical sciencePublic administrationGeographyBusinessLaw

Abstract

fetched live from OpenAlex

The degradation and collapse of the Earth’s ecosystems poses a formidable risk for humanity. Yet the effectiveness of political commitments to halt the irreversible loss of species and habitats remains critically low. The key challenge is to make the tough collective political decisions and then to follow through with real actions, despite often extreme resistance. What are the institutional mechanisms that can help increase the likelihood of the successful implementation of nature protection goals? Is decentralized, local-level governance more resilient in eventually meeting established nature protection goals than a centralized one? In attempting to answer these questions, this dissertation will rely on a qualitative analysis of nature protection policies carried out in New Zealand, Norway and British Columbia (Canada) between 1990 and 2012. In the final analysis the research will suggest the following. First, it appears that when dealing with protecting ecoregions defined by high opportunity costs, decentralized governance has very significant limitations that cannot be overcome without political coordination occurring at a higher-level. Among the most important factors for a meaningful adoption and gradual implementation is overcoming the initial discrepancy between the costs and benefits of conservation policies dividing the city and the countryside. A centralized governance offers distinct advantage in terms of bridging the divide between the countryside and the city and ensuring social partnership and cohesion between urban and rural populations over nature protection goals. Overall, resilient nature protection governance is likely to be centralized but one which allows the input of local stakeholders in both decision-making and especially at the stage of implementation. In addition, having open public access to land resources, including over privately owned lands, increases the likelihood of the implementation of conservation policies.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.959

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0140.012
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.230
Teacher spread0.224 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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