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Record W7133044230

Caring on the 'Inside': Tales of a Critical Educator in a (More) Punitive Space

2019· dissertation· W7133044230 on OpenAlexaboutno aff
Dargine Rajeswaran

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsPunitive damagesNarrativeSpace (punctuation)Economic JusticeWork (physics)Criminal justiceQualitative researchNarrative inquiry
DOInot available

Abstract

fetched live from OpenAlex

As a secondary-level educator with experiences in formal educational including mainstream, alternative, and programs in male correctional facilities, my learners seem to thrive because they feel cared-for. Ironically, I was never quite sure about what it means to be a caring educator. Through this narrative inquiry, I explore my experience teaching within two maximum security jails, in a metropolitan area of Canada. I explore and reflect on my pedagogical strategies and interactions to argue that caring teaching cannot fully interrupt/counteract the violence imposed by carceral systems but are capable of impacting individuals positively. This study, grounded in the narrative of teaching inside, considers how the procedures/expectations of jails work for and against caring pedagogies. I consider how it feels to teach within, how these learners identify me as a caring educator, and whether the teacher can sustain a caring pedagogy in a criminal justice system that enacts enduring harm.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.133
GPT teacher head0.519
Teacher spread0.386 · 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 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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