MétaCan
Menu
Back to cohort
Record W4390509984 · doi:10.18584/iipj.2023.14.3.14677

"We can do our own thing here on Haida Gwaii": The Haida Nation's response to COVID-19

2024· article· en· W4390509984 on OpenAlexaffvenue
Michaela McGuire

Bibliographic record

VenueInternational Indigenous Policy Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGovernment (linguistics)Corporate governanceCoronavirus disease 2019 (COVID-19)HistorySociologyPolitical scienceArchaeologyPublic administrationManagementMedicine

Abstract

fetched live from OpenAlex

The Council of the Haida Nation (CHN) is the National government of all Haida citizens—and their response to the COVID-19 pandemic on Haida Gwaii—is the central focus of this study. The CHN’s response is contextualized through an analysis of governance structures, consideration of previous epidemics, diseases, and health inequalities. The research questions for this project include: (1) How did the CHN’s role shift during the COVID-19 emergency response on Haida Gwaii; (2) What lessons can be garnered from the CHN’s response to inform future Haida Nation governance? To explore these research questions I conducted semi-structured, in-depth interviews with a sample of seven people who were living on Haida Gwaii during the pandemic and had some involvement with the CHN. Following an iterative process of data analysis, four main themes emerged from the data. These themes encompassed the inclusive approach taken by the CHN, the tireless work a small group of people did, and the importance of jurisdiction and self-determination while also considering lessons learned and capacity. The findings demonstrated the importance of continued pushes for self-determination as well as the ability of the CHN to expand its governance role.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.142
GPT teacher head0.421
Teacher spread0.280 · 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.

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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueInternational Indigenous Policy JournalSame topicClimate Change, Adaptation, MigrationFrench-language works237,207