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Record W4220757589 · doi:10.3390/su14073857

Relating Social and Ecological Resilience: Dutch Citizen’s Initiatives for Biodiversity

2022· article· en· W4220757589 on OpenAlexaff
R. During, Kristof Van Assche, R.I. van Dam

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcosystem dynamics and resilience
Canadian institutionsUniversity of Alberta
FundersMinisterie van Landbouw, Natuur en Voedselkwaliteit
KeywordsResilience (materials science)Socio-ecological systemCorporate governanceEcological resiliencePsychological resilienceEnvironmental resource managementEcological systems theorySociologySpace (punctuation)Diversity (politics)Value (mathematics)Environmental ethicsEcologyEnvironmental planningGeographyBusinessPsychologySocial psychologyEngineeringBiologyEconomicsComputer science

Abstract

fetched live from OpenAlex

Social resilience and ecological resilience are related and distinguished, and the potential of social resilience to enhance resilience of encompassing social-ecological systems is discussed. The value of resilience thinking is recognized, yet social resilience needs to be better understood in its distinctive qualities, while resisting identification of social resilience with one particular form of governance or organization. Emerging self-organizing citizen’s initiatives in The Netherlands, initiatives involving re-relating to nature in the living environment, are analyzed, using a systems theoretical framework which resists reduction of nature to culture or vice versa. It is argued that space for self-organization needs to be cultivated, that local self-organization and mobilization around themes of nature in daily life and space have the potential to re-link social and ecological systems in a more resilient manner, yet that maintaining the diversity of forms of knowing and organizing in the overall governance system is essential to the maintenance of social resilience and of diverse capacities to know human-environment relations and to reorganize them in an adaptive manner. Conclusions are drawn in the light of the new Biodiversity Strategy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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.

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

Citations11
Published2022
Admission routes1
Has abstractyes

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