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Record W4416482459 · doi:10.5040/9798216423881

Not Giving Up on People

2023· book· W4416482459 on OpenAlexaboutno aff
Barrett Emerick, Audrey Yap

Bibliographic record

VenueRowman & Littlefield eBooks · 2023
Typebook
Language
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPersonhoodWrongdoingHarmSolidarityRestorative justiceAction (physics)Economic JusticeSpace (punctuation)Moral imperative

Abstract

fetched live from OpenAlex

<JATS1:p>Feminist philosophers Barrett Emerick and Audrey Yap bring theoretical arguments about personhood and moral repair into conversation with the work of activists and the experiences of incarcerated people to make the case that prisons ought to be abolished. They argue that contemporary carceral systems in the United States and Canada fail to treat people as genuine moral agents in ways that also fail victims and their larger communities. Such carceral systems are a form of what Emerick and Yap call “institutionalized moral abandonment”. Instead, they argue that we should create communities of moral solidarity which open up space for wrongdoers to make up for their wrongs.</JATS1:p> <JATS1:p>As part of this argument, the book directly addresses one of the paradigm cases of wrongdoing often used to justify carceral systems: rape. Carceral systems that treat perpetrators of sexual violence as irredeemable monsters both obscure the reality of sexual violence and are harmful to everyone involved.</JATS1:p> <JATS1:p>As an alternative to carceral systems, Emerick and Yap argue for an orientation towards justice that is grounded in moral repair. This incorporates elements of restorative justice, mutual aid, and harm reduction. Instead of advocating for one specific and universal approach, the authors argue for multigenerational collective action that aims to build resilient communities that support the wellbeing of everyone.</JATS1:p>

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.590
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.005

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 head0.043
GPT teacher head0.302
Teacher spread0.260 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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