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Record W2979338208 · doi:10.4324/9781315149325-9

The dilemmas of placed compositional performances as methodology

2018· book-chapter· en· W2979338208 on OpenAlexaboutno aff
Anne Wessels

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComputer science

Abstract

fetched live from OpenAlex

This methodological reflection was catalyzed by a research project conducted in suburban Toronto inquiring into youth attitudes to diversity and the changing geography of the suburb. The first methodological dilemma concerns design when so much is still unknown as a research study begins. In addition to methodological adaptability, Wessels addresses the puzzles presented by empirical materials and their affective draw to the researcher. In the pre-analysis stage, although little sense can yet be made of the data and appropriate theoretical tools may not yet have been found, Wessels suggests the need for sufficient researcher time and space to adequately address ‘not knowing’, to read widely, and to adopt a methodology of patient waiting for appropriate and relevant theory. Wessels offers examples of methodological practices that evolved over the course of the research. In particular, ethnographic interviews-while-walking became a kind of walking methodology that finally became a placed compositional performance that included the participation of the nonhuman. These encounters and the empirical materials they yielded are discussed in relation to the theory of Deleuze, social geographers, and new materialists. Wessel concludes by considering the implications of placed compositional performances as a methodology that can reposition the human to include the nonhuman as agentive participant.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.941
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0300.001

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 head0.231
GPT teacher head0.461
Teacher spread0.230 · 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
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

Citations1
Published2018
Admission routes1
Has abstractyes

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