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Record W2787900321

Participation and democratization of knowledge: living theory research for reconciliation

2017· other· en· W2787900321 on OpenAlexaboutno aff
Jack Whitehead, Jacqueline Delong, Marie Huxtable

Bibliographic record

VenueInsight (University of Cumbria) · 2017
Typeother
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyEpistemologyFlourishingDemocratizationParticipatory action researchNarrativeRationalityDemocracyPsychologySocial psychologyPolitical scienceAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This presentation is intended to develop ideas from the 8th May 2015 ARNA Town Hall meeting in Toronto to the June 2017 ARNA conference in Cartagena, Colombia. It is focused on emerging understandings of knowledge democracy with convergences among those creating knowledge. We will show how Living Theorists draw on diverse approaches including living-cultures-of-inquiry, participatory frameworks, narrative inquiry, self-study and various forms of action research. Data from epistemologies of the South, East-Asian epistemologies and Western epistemologies, are analysed and used to show the mutual exclusion of different forms of rationality. In contrast to the exclusion expressed as ‘epistemicide’ by de Sousa Santos (2014) the living-logics of Living Theory research are used to show how different knowledges can be reconciled to contribute to the evolution of knowledge for the flourishing of humanity without denying the rationality of a different perspective. Multi-media narratives with digital visual data from a range of professional and community practices are used to clarify and communicate the meanings of embodied expressions of ontological and relational lifeaffirming values. These values are being used as explanatory principles in the explanations of individuals of their educational influences in their own learning, in the learning of others and in the learning of the social formations that influence practice and understandings.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.753
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.641
GPT teacher head0.606
Teacher spread0.034 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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