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Record W86522535 · doi:10.1177/117718011100700101

Story as Research Methodology

2011· article· en· W86522535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsStorytellingIndigenousScholarshipContext (archaeology)SociologyStory tellingNarrativeArtHistoryPolitical scienceLiteratureEcologyLaw

Abstract

fetched live from OpenAlex

Ubuntu storytelling is about engaging our relational selves. This is why my people the Ngoni say, “The story of one cannot be told without unfolding the story of many.” This means that the diverse and sometimes contradictory analysis of the same story is welcomed as long as it is exercised responsibly. If we relate to each other through storytelling then our Ubuntu storytelling is a research method. In this paper I share why and how using Ubuntu stories as methodology is an effective way to encourage Indigenous Ubuntu scholars to think about the endemic tools that make their scholarship accessible to our larger Black communities. The Ubuntu have always used the art of oral storytelling to extol the power of experience as a teaching tool because a story can allow a culture to regenerate itself. As a Maseko Ngoni, I highlight how we use Ubuntu storytelling to produce knowledge, by addressing the following themes: What Ubuntu storytelling is; why I use Ubuntu storytelling and how I address the challenges of using Ubuntu storytelling in a colonial context. I end with an example of an Ubuntu story.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.377
GPT teacher head0.518
Teacher spread0.142 · 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