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Record W3156362197 · doi:10.17645/si.v9i2.4347

Saving Lives: Mapping the Power of LGBTIQ+ First Nations Creative Artists

2021· article· en· W3156362197 on OpenAlexaboutno aff
Sandy O’Sullivan

Bibliographic record

VenueSocial Inclusion · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
Fundersnot available
KeywordsQueerIndigenousResistance (ecology)CreativityGender studiesSociologyPower (physics)Political scienceLaw

Abstract

fetched live from OpenAlex

In 2020, I was funded by the Australian Research Council to undertake research that examines the ways in which queer Indigenous creative practitioners create impact and influence. With a program titled “Saving Lives: Mapping the Influence of LGBTIQ+ First Nations Creative Artists,” the mapping is currently underway to explore how creativity has been used to demonstrate our reality and potential as queer First Nations’ Peoples. The title of this commentary explicitly reframes this from influence, to one of insistent resistance. It explores beyond how we persuade, to understand why the resistance in the work of First Nations’ queer creatives lays the groundwork for a future where the complexity of our identities are centred, and where young, queer Indigenous people can realise their own imaginings.

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)0.006
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0150.015
Scholarly communication0.0120.007
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.061
GPT teacher head0.299
Teacher spread0.238 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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