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Record W4230974198 · doi:10.1007/978-94-6091-481-2_1

Introduction

2011· book-chapter· en· W4230974198 on OpenAlexaff
Njoki Nathani Wane, Marlon Simmons

Bibliographic record

VenueSensePublishers eBooks · 2011
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsTransformative learningDialogical selfSociologyReflexivityIdeologyPoliticsPedagogyIndigenousEpistemologyStatus quoPsychologySocial scienceSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This collection is an outcome of teaching a course on cultural knowledge and colonial education for eight years. The course has created space for critical dialogical engagements with educators, learners, activists, and students involved in the process of reclaiming their Indigenous knowledge or making sense of their Indigeneity. A key to the many dialogues during class discussions has been to move the learning debates beyond the halls of academe or beyond goals of bringing about change that focus on issues of cognition, inclusion, discrimination and integration, to an emphasis on critical self-reflexivity that would allow for the interrogation of individual beliefs, values, biases and hence, work towards uncolonizing the mind. The dialogues have taken into account the social, political and cultural changes that impede transformation, and have called for a rethinking of the dominant seductive ideologies that serve to marginalize other people’s ways of knowing. The course readings have pointed to different ways of conceptualizing and engaging in transformative learning and uncolonizing procedures. The readings attempted to challenge the status quo and offer alternative ideas and interpretations that allow for the dismantling of the persistent ambiguous connections between the known and the unknown; the self and the constructed other.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.841
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.254
Teacher spread0.231 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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