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Record W4395687962 · doi:10.1016/j.envsci.2024.103773

The split ladder of participation: A literature review and dynamic path forward

2024· review· en· W4395687962 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.

Bibliographic record

VenueEnvironmental Science & Policy · 2024
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsUniversity of Regina
FundersHorizon 2020European Research CouncilSocial Sciences and Humanities Research Council of CanadaH2020 European Research CouncilCanada Research ChairsEuropean Commission
KeywordsPath (computing)Computer sciencePath dependentBusinessEconomicsMathematical economicsComputer network

Abstract

fetched live from OpenAlex

Participation of people in decision making and tackling complex problems where there is lack of consensus on the science and relevant values continues to be an important research topic. The 2015 Split Ladder of Participation offered a diagnostic and methodological framework cited in 162 papers. This paper addresses the question: What does a literature review of the Split Ladder of Participation reveal about engaging people in policy problems, effecting transformational change, and how can this diagnostic and strategic tool be improved? A systematic literature review revealed papers that disclose transformational change, or triple loop learning requires: strong social science; social and natural interdisciplinary science; and considerations of uncertainty in environmental science together with uncertainty of values and considerations of power. Policy problems with low levels of trust offer opportunities to engage interest and participation in their resolution. Governments over-utilizing methods limiting participation, may lead to lock-in. Focusing on complex, interconnected problems through participation creates an enduring policy and science, interdisciplinary innovation space. Recognizing participation that is plural, amorphous, and fluid draws attention to power, multiple stakeholder framings of complex issues, advances social learning changing values, norms, power, and the very ethics of science (where social and natural/physical scientists acknowledge and share their power with people), and ultimately advances environmental justice.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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