MétaCan
Menu
Back to cohort
Record W2902378522 · doi:10.5751/es-10385-230434

Systemic resilience: principles and processes for a science of change in contexts of adversity

2018· article· en· W2902378522 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEcology and Society · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
FundersRoyal Roads UniversitySocial Sciences and Humanities Research Council of CanadaUniversity of PretoriaCanadian Institute for Advanced Research
KeywordsResilience (materials science)Environmental resource managementClimate changeEnvironmental ethicsPsychological resilienceSociologyEpistemologyEnvironmental planningPolitical scienceEcologyGeographyPsychologyEnvironmental scienceSocial psychologyBiology

Abstract

fetched live from OpenAlex

Despite the increasing popularity of discussions of resilience in disciplines as diverse as ecology, psychology, economics, architecture, and genetics (among many others), researchers still lack a conceptual model to explain how the resilience of one system relates to the resilience of other cooccurring systems. Models that explain resilience within a single system are more robust and better studied. Although some researchers argue that both ontological and epistemological weaknesses prevent such an integrated model from being developed (the incommensurability hypothesis), others have carried out metasyntheses using techniques like network citation analysis to identify common principles and processes that are associated with resilience across disciplines. Although useful, metasyntheses have yet to identify sufficient commonalities across bodies of research to account for a single model of resilience. This paper adapts methods used for the thematic synthesis of qualitative data to critically analyze metasyntheses of resilience and identify principles that explain patterns of resilience of different systems (biological, psychological, social, cultural, economic, legal, communication, and ecological systems are all considered). Sixteen purposefully selected published syntheses were reviewed, along with dozens of other supporting peer-reviewed articles and book chapters, supplemented by consultations with knowledge experts. Seven common principles across systems were identified. These include: (1) resilience occurs in contexts of adversity; (2) resilience is a process; (3) there are trade-offs between systems when a system experiences resilience; (4) a resilient system is open, dynamic, and complex; (5) a resilient system promotes connectivity; (6) a resilient system demonstrates experimentation and learning; and (7) a resilient system includes diversity, redundancy, and participation. Where evidence refutes a principle, discordant findings are highlighted. Together, these principles account for resilience as a sequence of systemic interdependent interactions through which actors (whether persons, organisms, or ecosystems) secure the resources required for sustainability in stressed environments.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.050
GPT teacher head0.393
Teacher spread0.344 · 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