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Record W6945516072 · doi:10.25607/obp-1694

Wildlife Management Summit Report November 6–8, 2017 Ottawa, Canada.

2018· report· en· W6945516072 on OpenAlexaboutno aff

Bibliographic record

VenueIOC of UNESCO (Intergovernmental Oceanographic Commission) · 2018
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSummitCircumpolar starWildlifeWildlife managementArcticInterimPeninsulaWhite paperFood security

Abstract

fetched live from OpenAlex

The Inuit Circumpolar Council (ICC) hosted the Wildlife Management Summit that took place on November 6 to 8, 2017 in Ottawa, Ontario, Canada to deliver on the commitment made in Article 40 of the Kitigaaryuit Declaration, as adopted at the 2014 ICC General Assembly in Inuvik, which, “directs ICC to plan and host an Inuit summit on wildlife management.” The ICC Wildlife Management Summit’s goal was to examine the influence that policies (international, regional, national instruments), environmental change, public perceptions, and changing social economic conditions in the Arctic are having on Arctic wildlife and Inuit food security. The Summit was further directed by the Alaskan Inuit Food Security Conceptual Framework: How to Assess the Arctic From an Inuit Perspective. The report, which reflects the views and knowledge of Alaskan Inuit, emphasizes the need to build stronger co-management structures in order to support food security. The following key actions were put forward by summit participants: -- ICC establish and support a Circumpolar Inuit Wildlife Committee (CIWC) whose mission will be to collaboratively, cooperatively and inclusively preserve and protect Inuit cultural rights to food sovereignty by providing a unified pan-Arctic Inuit voice. -- ICC establish and support a Circumpolar Inuit Wildlife Network (CIWN) in order to support information sharing, learning and communication about Inuit rights, wildlife management and food sovereignty within the network and with the CIWC. -- That an interim steering committee be formed immediately to develop a strategy for CIWC to be proposed to the General Assembly of ICC in July 2018.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.263
Threshold uncertainty score0.878

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.001
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2630.093

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

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