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Record W4295846750 · doi:10.1111/rec.13789

Awareness and use of the Society for Ecological Restoration's International Principles and Standards for the Practice of Ecological Restoration in Canada

2022· article· en· W4295846750 on OpenAlexafffundabout
Sonia A. Voicescu, John‐Francis Lane, Steven J. Cooke, Eric Higgs, Alina C. Fisher, Line Rochefort, Nancy Shackelford, Stephen D. Murphy

Bibliographic record

VenueRestoration Ecology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversité LavalUniversity of WaterlooCarleton UniversityUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRestoration ecologyDisconnectionEcologyValue (mathematics)Work (physics)Best practiceEnvironmental resource managementPsychologyPolitical scienceEnvironmental scienceEngineeringComputer scienceBiologyLaw

Abstract

fetched live from OpenAlex

The Society for Ecological Restoration (SER) published the second edition of its International Principles and Standards for the Practice of Ecological Restoration in 2019. We conducted a pan‐Canadian study using semi‐structured interviews with restoration professionals to explore the extent to which restoration practitioners are aware of the document and use it. Overall, we found that direct uptake of the document by practitioners was lower than expected, with approximately 37.7% of all participants that were both aware of and consulting the publication for guidance in their practice of ecological restoration. This is due in part to low awareness of the document itself, with only a small majority (56.5%) of interviewees being aware of it. Other reasons listed by practitioners such as the structure of the publication, its added value, and its suitability for on‐the‐ground work revealed why some individuals aware of the existence of the document still failed to consult it. Here, we present a more nuanced assessment of these observations and share our findings with the ecological restoration community to address this disconnection. With intensifying pressures to achieve restoration success internationally, SER's guidance is critical. We analyze why it seems guidance from SER is not being taken up as fully as it might, and ways in which future versions may be improved.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.991

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 studies0.0000.000
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 head0.045
GPT teacher head0.290
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2022
Admission routes3
Has abstractyes

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