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Record W4410078630 · doi:10.1016/j.cosust.2025.101536

Leveraging place-based identities and senses of belonging to mobilize for action-oriented research in UNESCO sites

2025· article· en· W4410078630 on OpenAlexafffund
Katja Malmborg, Jacqueline M. Hamilton, Carolin Seiferth

Bibliographic record

VenueCurrent Opinion in Environmental Sustainability · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsMcGill University
FundersEuropean CommissionNatural Sciences and Engineering Research Council of CanadaHORIZON EUROPE European Innovation EcosystemsHORIZON EUROPE Framework ProgrammeSvenska Forskningsrådet FormasNorges Forskningsråd
KeywordsAction (physics)Action researchGeographyPolitical scienceSociology

Abstract

fetched live from OpenAlex

With increasing land-use pressures on landscapes, it is critical to improve their governance while being inclusive of those living there. United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage sites and Biosphere Reserves play a crucial role in protecting both social and ecological values in designated landscapes, making them interesting sites for action-oriented research. The designation and maintenance of these protected areas can form and reshape the place-based identities and senses of belonging held by local actors and consequently enable or restrain the process of mobilizing action for sustainability. In this review, we build on recent literature and our own experiences of research in UNESCO sites to propose place-based identities and senses of belonging as potential deep leverage points that may be acted on to achieve transformative action-oriented research for sustainability while also reflecting on our own positionality before and throughout the research process.

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 score0.333
Threshold uncertainty score0.437

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 head0.175
GPT teacher head0.382
Teacher spread0.207 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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