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Record W4308025760 · doi:10.1080/26395916.2022.2133173

The programme on ecosystem change and society (PECS) – a decade of deepening social-ecological research through a place-based focus

2022· article· en· W4308025760 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.

Bibliographic record

VenueEcosystems and People · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsMcGill University
FundersSvenska Forskningsrådet Formas
KeywordsTransformational leadershipSustainabilityReflexivityAction researchAction (physics)Social changeSociologyPerspective (graphical)Political scienceEcologySocial sciencePublic relationsComputer science

Abstract

fetched live from OpenAlex

The Programme on Ecosystem Change and Society (PECS) was established in 2011, and is now one of the major international social-ecological systems (SES) research networks. During this time, SES research has undergone a phase of rapid growth and has grown into an influential branch of sustainability science. In this Perspective, we argue that SES research has also deepened over the past decade, and helped to shed light on key dimensions of SES dynamics (e.g. system feedbacks, aspects of system design, goals and paradigms) that can lead to tangible action for solving the major sustainability challenges of our time. We suggest four ways in which the growth of place-based SES research, fostered by networks such as PECS, has contributed to these developments, namely by: 1) shedding light on transformational change, 2) revealing the social dynamics shaping SES, 3) bringing together diverse types of knowledge, and 4) encouraging reflexive researchers.

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)0.003
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
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 head0.064
GPT teacher head0.284
Teacher spread0.221 · 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