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Record W7006853056

What Is Happening Where? An Evaluation of Social Science Research Trends in Nunavut (2004-2019)

2022· dissertation· en· W7006853056 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsSocial researchGeneral partnershipThematic analysisScope (computer science)Community engagementTracking (education)Diversity (politics)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

Many Inuit feel they are not benefitting from research activities that come from colonial research licensing practices and laws enabling state control over research. In Nunavut, research licensing also helped to increase community engagement in research. The Nunavut Research Institute (NRI), based in Iqaluit, Nunavut manages research and issues physical/natural, health, and social science research licenses in the Territory. In partnership with the NRI, we examined social science and Inuit knowledge research licensed between 2004-2019, to understand the scope of research trends in Nunavut. Using the 568 project summaries from social science research licenses, thematic content analysis was conducted to: i) identify research topics in social science and Inuit knowledge projects; ii) determine frequency and diversity of topics according to leadership, location, and timeframe; iii) develop new metrics to improve tracking of research topics; and, iv) contribute to the development of a Nunavut research portal making NRI research applications/reports public. Through this analysis we learned that social science research in Nunavut increased over time. Research projects are predominantly led by Canadian academics, with the highest concentration of research being in Iqaluit. Social science research is mainly focused on cultural topics, conducted using interviews, and shared in peer-reviewed journal articles. Community engagement has also increased over time in Nunavut, and research intensity appears to be connected to the availability of research-related capacity and infrastructure in a community. This research is an important starting point in making research trends more accessible to Nunavummiut (people of Nunavut), and more useable by decision-makers regarding research intensity and potential fatigue in some Nunavut communities. Long term, improving tracking of metrics such as funding sources and reporting mechanisms can contribute to policy reform and to advancing the NRI licensing database. This is an initial step contributing to Nunavut-specific approaches to Inuit self-determination in research.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.3550.000

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 head0.109
GPT teacher head0.390
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 designOther design
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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