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Record W4362509194 · doi:10.1353/nai.2023.0017

Dadibaajim: Returning Home through Narrative by Helen Olsen Agger

2023· article· en· W4362509194 on OpenAlexaboutno aff
Wendy Makoons Geniusz

Bibliographic record

VenueNative American and Indigenous Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeIndigenousHistorySociologyVariety (cybernetics)Media studiesLiteratureArtComputer science

Abstract

fetched live from OpenAlex

Reviewed by: Dadibaajim: Returning Home through Narrative by Helen Olsen Agger Wendy Makoons Geniusz (bio) Dadibaajim: Returning Home through Narrative by Helen Olsen Agger University of Manitoba Press, 2021 there are far too many wonderful things to say about Dadibaajim in this short review. Focusing on the Namegosibii Trout Lake community (Ontario), Agger’s text is a beautifully laid-out miikaanens (trail) that other Indigenous scholars could follow to write about their own communities and research. Agger provides instruction on important protocols for working with elders, which will be useful to a variety of audiences, especially those working in and with Indigenous communities and those working with previously collected dadibaajim narratives. Agger’s text also warns about the problems of prior research, especially that done by outsiders, on Indigenous communities. These warnings can aid scholars from all backgrounds, as well as policy-makers, who sincerely wish to work with Indigenous communities to create a decolonized, reconciled future. The only warning I have for prospective readers of Dadibaajim is that it is an academic text, clearly written for academics. While that is a wonderful prospect for my colleagues hoping to find an invigorating text for their Indigenous research methodologies courses (yes, this is it!), I hope Agger writes another version of this text that is accessible to a wider audience. I also have one correction to make. The phrase “Gego zhaaganaashiiyaadizisiidaa” is not, as Agger states, a phrase used by the elders my mother worked with at Seven Generations Educational Institute. It is simply a title of a presentation I gave at Anishinaabewin Niswi (131). I was modifying the verbs: wemitigoozhiiwaadizi and zhaagnaashiiyaadizi, both of which that group of elders used and both of which refer to being colonized, living as a white person at the expense of being Anishinaabe. Throughout her text, Agger advocates, quite eloquently, for Anishinaabemowin, Ojibwe, and other Indigenous languages and oral narratives: “It is important to keep in mind that effective forms of knowledge transmission existed long before Europeans imposed literatism. The text is a human construction, neither natural nor neutral” (63). She emphasizes the necessity of Indigenous language revitalization being a part of all decolonization efforts: “Use of English or other colonial languages perpetuates the domination [End Page 109] of the wemitigoozhiiwaadiziwin way of thinking” (36). Agger’s arguments make a compelling case for having substantial Indigenous language requirements as part of all Indigenous studies degrees; they are a rallying cry for those of us who can research and publish in our Indigenous languages to do so now, before we lose any more of our first-language speakers and before we are presented, yet again, to the world in words that are not our own and in languages that can, at best, only summarize key concepts of our philosophies. Agger’s text itself will contribute to language revitalization efforts. As a language learner and educator, I am grateful for the amount of space in this text that Agger and her editors dedicate to transcriptions of first-language Ojibwe speech. All too often, we only get translations of elders’ words, rather than being able to read what they actually said in their languages. Agger shares an entire chapter of dadibaajim related to place names that had not been previously documented. This section contains invaluable material on teachings, fluency patterns, and information for other language and culture revitalization and research. For several decades in Canada and the United States we have been going through a strong period of Indigenous cultural revitalization, in which some teachings have been embraced as “pan-Indian” or, more recently, “pan-Indigenous.” When these teachings differ from those in a particular community, the older teachings are often replaced. I have seen this throughout my lifetime. Agger gives examples of how some of today’s widely accepted pan-Indigenous teachings of are not part of traditional Namegosiibii Anishinaabe culture. She notes that Sweet Grass is “not a traditional component of Namegosiibii Anishinaabe cultural practice” (40). The concepts of Turtle Island and Mother Earth were not recognized by elders in her community (36). Her statements make a strong case for the importance of recording and retaining the diversity within our Indigenous communities, including the diversity...

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0330.009

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 head0.032
GPT teacher head0.368
Teacher spread0.336 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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