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Record W4415820389 · doi:10.33682/g47y-4kbh

Inday Dolls: Body Monologues and Lullabies for Freedom in Prison: Scripting Possible Futures in Justice Art in Iloilo's Correctional System

2019· article· en· W4415820389 on OpenAlexaff
Ma Rosalie Abeto Zerrudo, Dennis Gupa

Bibliographic record

VenueArtsPraxis · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPrisonPerformative utteranceNarrativeStorytellingPoliticsEconomic JusticeCompassionLiminality

Abstract

fetched live from OpenAlex

The prison is not a dead end. Freedom is born in prison. Women in prison bounce back, resurrecting through their stories, reclaiming their bodies. This research investigates the politics of freedom, space, and body in prison. Women exercise their own sense of freedom navigating in a tight small crowded place through stories of objects, body lullabies, and archetypal ethnodrama. Women recreated new selves with new colors to light up their life in the darkest times. Storytelling as a powerful tool for political and cultural assertion is essential in this research as a healing art process. The creative personal geography work makes women tell stories as a means of gathering parts of themselves back to one piece. Our work in freedom art we resonate to the words of Estés, "Stories are medicine… They have such power…we need only to listen… Stories are embedded with instructions which guide us about the complexities of life" (Estés p 15-16). This performance research presents the body monologues of women in a space (read: prison) where time restricts liberty and memories of freedom collapse with dreams of emancipation. Through a series of creative and performative exercises this prison became a performance space animated with the living narratives of human stories of objects and as a site of compassion where an overflowing bodies intersected and shared the politics of tolerance, compassion and love.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.016
GPT teacher head0.290
Teacher spread0.274 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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