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Record W4318184300 · doi:10.1007/s13412-022-00811-8

Exploring the role of boundary work in a social-ecological synthesis initiative

2023· article· en· W4318184300 on OpenAlexafffund
Barbara Schröter, Claudia Sattler, Jean Paul Metzger, Jonathan R. Rhodes, Marie‐Josée Fortin, Camila Hohlenwerger, L. Román Carrasco, Örjan Bodin

Bibliographic record

VenueJournal of Environmental Studies and Sciences · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversity of Toronto
FundersAustralian Research CouncilNatural Sciences and Engineering Research Council of CanadaBundesministerium für Bildung und ForschungCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCanada Research ChairsConselho Nacional de Desenvolvimento Científico e TecnológicoBiodiversa+
KeywordsBoundary-workBoundary objectMultidisciplinary approachBoundary (topology)Work (physics)Identification (biology)Leverage (statistics)Knowledge managementBoundary spanningComputer scienceSociologyManagement scienceEnvironmental resource managementEcologyEngineeringNegotiationEnvironmental scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Inter- and transdisciplinary collaboration in environmental studies faces the challenge of communicating across disciplines to reach a common understanding of scientific problems and solutions in a changing world. One way to address current pressing environmental challenges is to employ a boundary work approach that uses activities across borders of separated field of research. But how can this look like in practice? In this research brief, we self-evaluated the boundary work approach in a synthesis group on socio-ecological systems, based on an online survey with participants. Here, we discuss how boundary work can be used to integrate the knowledge from natural and social scientists both working on social-ecological systems. We found participants were selected to be acted as boundary spanners and were willing to cooperate for solving multidisciplinary issues regarding the understanding, management, and maintenance of ecosystem services. A social-ecological network analysis framework served as a boundary concept and object for communication and knowledge integration. Being familiar with a joint boundary concept like ecosystem services prior to the working group event supported the communication of participants. These results indicate that synthesis initiatives could strategically leverage boundary work through the careful selection of members, with the inclusion of boundary spanners, as well as prior joint identification of boundary concepts and objects.

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)0.000
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 score0.030
Threshold uncertainty score0.318

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 studies0.0000.000
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 head0.092
GPT teacher head0.263
Teacher spread0.172 · 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

Citations11
Published2023
Admission routes2
Has abstractyes

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