MétaCan
Menu
Back to cohort

“Justice for Native People, Justice for Native Me”

2021· book-chapter· en· W4289717924 on OpenAlexaboutno aff
Jillian Fish, Payton K. Counts

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook-chapter
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousStorytellingNarrativeColonialismMetisEconomic JusticeNative americanSociologyGenealogyMedia studiesAnthropologyHistoryPolitical scienceArtLawLiteratureArchaeology

Abstract

fetched live from OpenAlex

Native American and Indigenous peoples are the original inhabitants of the U.S., including hundreds of tribes with distinct cultures and histories that inform their epistemological (i.e. ways of knowing) and ontological (i.e. ways of being) worldviews. Despite this, Western peoples continue to <italic>story</italic> the experiences of Native peoples for them, creating master narratives in which Native peoples are relics of the past, and impoverished, uneducated, drunkards in the present. Indeed, this is a longstanding effect of the colonial project that continues to erase the authentic, lived experiences of Native peoples, thus limiting their self-understanding and future possibilities. To counter these enduring colonial narratives, it is critical Native peoples have access to both <italic>Native-centered</italic> and <italic>community-based</italic> spaces in which the complexities of Native identities and experiences can be voiced and storied. <italic>OrigiNatives</italic> sought to provide urban Native peoples in Minnesota a space that privileged their ways of knowing and being through digital storytelling workshops, in which Native peoples (<italic>n</italic> = 75) from thirty-four different tribal communities created original and authentic stories of their cultures, histories, and lives using digital media technologies. This chapter reviews the process of creating and implementing <italic>OrigiNatives</italic> through partnerships with Native-serving organizations in Minnesota, highlighting implications that digital storytelling methodologies have for challenging and resisting coloniality by empowering Native peoples to tell <italic>our stories, our way</italic>.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.103
GPT teacher head0.348
Teacher spread0.244 · 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 designNot applicable
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

Citations19
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicDigital Storytelling and EducationFrench-language works237,207