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Record W4388428305 · doi:10.1521/jsyt.2023.42.2.1

Our Bodies as Multi-storied Communities: Ethics and Practices

2023· article· en· W4388428305 on OpenAlexvenueno aff
Poh Lin Lee

Bibliographic record

VenueJournal of Systemic Therapies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsUnpackingSociologyPosition (finance)EpistemologyEnvironmental ethicsEngineering ethicsPublic relationsAestheticsPolitical scienceEngineeringArtBusinessPhilosophy

Abstract

fetched live from OpenAlex

In this article, I introduce and develop an outline of the ethics and practices that invite us to recognize our bodies as multi-storied communities and to engage in decolonial feminist co-research. In discussing how we might come to these practices I share multimedia fragments of co-research, alongside a person I'm consulting with. This gives the reader the chance to see these ideas and practices in the journey of becoming rather than from a position of having reached a certain destination. This article offers a unique way of unpacking therapy sessions together with the person at the center and demonstrates the need to question the very notion of our bodies as singular and how that affects our practice. It contributes to the literature by calling into question taken-forgranted notions of our body and thereby how to engage, involve, and connect with body-inclusive practices in therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0190.199
Scholarly communication0.0220.016
Open science0.0020.018
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0030.001

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 head0.281
GPT teacher head0.418
Teacher spread0.137 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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