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Record W4405370596 · doi:10.1080/1554480x.2024.2435921

Movement, movie-making, and soil art: hope in affectively de/composing pedagogies

2024· article· en· W4405370596 on OpenAlexaff
Michelle A. Honeyford, Jennifer Watt, Noah Cain, Katya Adamov Ferguson

Bibliographic record

VenuePedagogies An International Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsMeaning (existential)Meaning-makingSociologyMovement (music)DancePedagogyMotion (physics)AestheticsVisual artsEpistemologyPsychologyComputer scienceArt

Abstract

fetched live from OpenAlex

In the complexities of current realities, we are a writing collective of educators interested in placing hope in the present, particularly in composing practices and pedagogies. Drawing on a post-qualitative methodology, we weave together examples of practices of dance/movement, digital movie-making, and soil artivism with specific concepts of affect-as/is-hope. As a counternarrative to writing pedagogies and assessments that are increasingly standardized, product-oriented, technical, rational, and disembodied, we introduce the term de/composing pedagogies to conceptualize the potential in processes of becoming/making/meaning-making that are always something else/more/different and even less. De/composing pedagogies help us name, describe, experience, and examine – individually and collectively – what is moving us and our practices more intensely and deeply; what is making possible new ways of being/becoming/doing for us and for our co-learners (e.g. the teachers and students we work with); and what is expanding potential for us as writers/composers/educators in and across various situations and contexts. As (re)sources of hope, we close with pedagogical questions related to composing through/with elements of experimentation, embodiment, an emphasis on relation and (re)connection, ephemeral and material elements, (e)motion, and the emergence of meaning-making.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.431
Teacher spread0.366 · 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 designTheoretical or conceptual
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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