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Record W2964192637 · doi:10.1017/9781316443712

The Neuroethics of Memory: From Total Recall to Oblivion

2019· book· en· W2964192637 on OpenAlexaff
Walter Glannon

Bibliographic record

Venuenot available
Typebook
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNeuroethicsRecallMisattribution of memoryAgency (philosophy)ObligationPsychologyReconstructive memoryFalse memoryCognitive scienceCognitive psychologyChildhood memoryNeuroscienceCognitionPolitical scienceSociologySemantic memoryLawSocial science

Abstract

fetched live from OpenAlex

The Neuroethics of Memory is a thematically integrated analysis and discussion of neuroethical questions about memory capacity and content, as well as interventions to alter it. These include: how does memory function enable agency, and how does memory dysfunction disable it? To what extent is identity based on our capacity to accurately recall the past? Could a person who becomes aware during surgery be harmed if they have no memory of the experience? How do we weigh the benefits and risks of brain implants designed to enhance, weaken or erase memory? Can a person be responsible for an action if they do not recall it? Would a victim of an assault have an obligation to retain a memory of this act, or the right to erase it? This book uses a framework informed by neuroscience, psychology, and philosophy combined with actual and hypothetical cases to examine these and related questions.

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.021
Scholarly communication0.0050.009
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.002

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 head0.077
GPT teacher head0.315
Teacher spread0.238 · 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
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

Citations4
Published2019
Admission routes1
Has abstractyes

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