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Record W2570731680 · doi:10.1111/japp.12256

Why Childhood is Bad for Children

2017· article· en· W2570731680 on OpenAlexaff
Sarah Hannan

Bibliographic record

VenueJournal of Applied Philosophy · 2017
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsUniversity of ManitobaResearch Manitoba
Fundersnot available
KeywordsVulnerability (computing)Childhood studiesIdentity (music)CriticismPsychologyEarly childhoodDevelopmental psychologySocial psychologySociologyLawPolitical scienceAestheticsComputer security

Abstract

fetched live from OpenAlex

Abstract This article asks whether being a child is, all things considered, good or bad for children. I defend a predicament view of childhood, which regards childhood as bad overall for children. I argue that four features of childhood make it regrettable: impaired capacity for practical reasoning, lack of an established practical identity, a need to be dominated, and profound and asymmetric vulnerability. I consider recent claims in the literature that childhood is good for children since it allows them to enjoy special goods that aren't available in adulthood, or which are harder to access in adulthood. I raise some difficulties for these claims. Then I argue that whatever version of these views survives my criticism will not establish that childhood is overall good for children. This is because the goods of childhood aren't significant enough to outweigh the bad features associated with being a child. I conclude by suggesting that the badness of childhood for children means that we are likely to owe more to children than to adults.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.007
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.036
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.345
Teacher spread0.310 · 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

Citations69
Published2017
Admission routes1
Has abstractyes

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