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Record W4410493654 · doi:10.1002/pan3.70056

Cultivating reciprocity and supporting Indigenous lifeways through the cultural transformation of natural resource management in North America

2025· article· en· W4410493654 on OpenAlexaff
Jonathan Fisk, Richard E. W. Berl, Jonathan W. Long, Lara A. Jacobs, Lily M. van Eeden, Melinda M. Adams, Álvaro Fernández‐Llamazares, Michael C. Gavin, Christopher K. Williams, Jonathan Salerno, Bas Verschuuren, Nathan Bennett, Rodrigue Idohou, Alexander Mawyer

Bibliographic record

VenuePeople and Nature · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersDivision of Graduate Education
KeywordsIndigenousReciprocity (cultural anthropology)Natural resourceNatural resource managementResource (disambiguation)Transformation (genetics)Natural (archaeology)GeographyEnvironmental ethicsEnvironmental resource managementSociologyEthnologyAnthropologyPolitical scienceEcologyArchaeologyEconomicsComputer scienceBiologyLaw

Abstract

fetched live from OpenAlex

Abstract Recent decades have seen increasing calls for implementing Indigenous Knowledges (IK) in natural resource management (NRM). However, efforts have been limited by the cultural incommensurabilities between (1) NRM institutions, which are rooted in worldviews that prioritize extraction for dominant cultures and assume dominance over nature and (2) Indigenous worldviews that prioritize kincentric reciprocity with the environment. This manuscript addresses how transforming NRM institutions enables management to better support Indigenous Knowledges and lifeways. This manuscript examines incommensurabilities between NRM institutional cultures and Indigenous cultures, with the value and lifeway of reciprocity as the focal point. Through synthesizing interdisciplinary scholarship and examples from author experiences, we explore how NRM institutions in North America can transform to honour and facilitate reciprocity, especially within efforts to implement IK and support Indigenous lifeways. NRM institutions are cultural products, and in North America were born of colonial histories and cultural roots connected to modern governance and power dynamics. These cultural foundations led to NRM approaches that prioritize maximizing economic growth while guarding against overexploitation. Kincentric reciprocal relations with the environment often emphasize interdependency with more‐than‐human kin, place‐based holistic Knowledges grounded in cultural practices and communal responsibility to cultivate social‐ecological abundance for present and future generations. Incommensurabilities between NRM institutional cultures and Indigenous cultures impede efforts to implement IK and support Indigenous lifeways as: (1) rigid institutional structures do not account for Indigenous worldviews and values but instead attempt to fit IK within dominant paradigms; (2) the siloing of NRM leads to the piecemealing and invalidation of IK at the expense of Knowledge Holders and (3) ineffective public engagement strategies limit the possibility of reciprocal relations between NRM institutions and communities throughout management processes. Transforming NRM institutional cultures to better implement IK and support Indigenous lifeways is key for redressing long‐standing issues and ensuring social‐ecological resilience and abundance. Heavy investments of time, personnel and resources are necessary for transforming NRM institutions to appropriately cultivate reciprocal relations with Indigenous communities and lands. Strategies towards transformation include decentralization through decolonial frameworks, knowledge co‐production and using place‐based cultural evaluation processes to improve cultural alignment. Read the free Plain Language Summary for this article on the Journal blog.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.016
Scholarly communication0.0040.003
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.345
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations12
Published2025
Admission routes1
Has abstractyes

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