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Record W4400134265 · doi:10.1002/jwmg.22625

Special issue: Indigenous research and co‐stewardship of wildlife

2024· article· en· W4400134265 on OpenAlexaboutno aff
Jonathan H. Gilbert, Michel T. Kohl

Bibliographic record

VenueJournal of Wildlife Management · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsStewardship (theology)WildlifeIndigenousEnvironmental stewardshipEnvironmental planningEnvironmental resource managementWildlife managementGeographyPolitical scienceEnvironmental ethicsEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

Indigenous People have occupied the North American continent since time immemorial, and yet, most North Americans are unaware of the sheer number or diversity of Indigenous groups or the scale of the landscape they manage and influence (Thorstenson 2023).To provide some context, the Indigenous groups of just the United States and Canada oversee over 850,000 km 2 of land, an area larger than all but 34 of the world's countries.These vast landscapes hold a plethora of culturally and economically important natural resources.For example, in the United States, Indian Nations manage over 178,000 km 2 of rangelands, 72,000 km 2 of commercial forests, and 16,000 km of streams and rivers, all of which provide important habitat for fish and wildlife populations, including >500 threatened and endangered species (Thorstenson 2023).The management of these resources varies because of the diversity of values, goals, and perspectives of the unique groups that have resided here for millennia.To exemplify this, we briefly describe the diversity of Indigenous groups that reside in North America within the context of government recognitions.Each of these groups are considered sovereign entities with government-to-government relationships.Thus, differences in Indigenous culture, history, policy, and legal designations all merge to create diversity and complexity across Indigenous Fish and Wildlife Management agencies responsible for the management of these wildlife resources (Stricker et al. 2020, Hoagland and Albert 2023).In the United States, Indigenous Peoples are generally divided into 3 groups: those that belong to a state or federally recognized tribe, descendants of state or federally recognized tribes without membership or recognition from the tribe, or descendants of a tribe that has no legal recognition.There are 574 federally recognized tribes, which are commonly separated into 2 groups: those within the contiguous states (i.e., Native American, Indian) and Alaskan Native.This delineation is due to the recent timing in which Alaska was settled, and the lack of treaties established between Alaskan tribes and the United States Government.These groups are separate from other nonfederally recognized Indigenous groups such as Native Hawaiians, which are of Polynesian descent.In Canada, Indigenous groups are commonly identified as First Nations, Inuit, or Métis.First Nations refers to the Indian people recognized by the Canadian Constitution, regardless of their status as federally recognized.The governing units that make up First Nations groups, referred to as bands, are the equivalent of Native American tribes in the United States.Inuit are the Indigenous groups that reside across Arctic Canada who did not sign treaties with the Canadian Government but have negotiated modern land claims.Métis are people of mixed First Nation and European ancestry who have no current federal recognition status but have a unique culture different from both Inuit and First Nations.Indigenous groups in Mexico are also unique.They do not have clear legal recognition at a state or federal level, clarity on their rights to hold title to land, or access to traditional land bases.It is important to consider this diversity and complexity across Indigenous groups because of the ever-growing interest and awareness of Indigenous Knowledge (IK).Such IK is increasingly being recognized and sought out as part of wildlife management and conservation solutions (Gadgil et al. 2022).The IK held by Indigenous people can enhance our understanding of wildlife and their habitats (Popp et al. 2019) and local IK can fill gaps in scientific understanding that may be difficult to obtain through other means (Stern and Humphries 2022).Indigenous Knowledge provides information that has been collected over lifetimes and the use of IK and Western science (WS) together will yield more comprehensive information about wildlife species than either method alone (Service et al. 2014).

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.163
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0050.003
Scholarly communication0.0120.009
Open science0.0040.005
Research integrity0.0140.008
Insufficient payload (model declined to judge)0.1630.042

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 head0.084
GPT teacher head0.439
Teacher spread0.356 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2024
Admission routes1
Has abstractyes

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