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Record W1492455475 · doi:10.37693/pjos.2013.4.8841

Tattoos as Narratives: Skin and Self

2013· article· en· W1492455475 on OpenAlexaffvenueabout
Chris William Martin

Bibliographic record

VenuePublic Journal of Semiotics · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicTattoo and Body Piercing Complications
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNarrativeSemioticsAgency (philosophy)Statement (logic)Meaning (existential)AestheticsIdentity (music)SociologyEpistemologyEphemeral keyPerceptionSelfExpression (computer science)ArtPhilosophySocial scienceLiterature

Abstract

fetched live from OpenAlex

This article explores the polysemic nature of contemporary tattoos by comparing interviewees‘ perceptions of the meanings of their tattoos with the meanings which can be imputed to them by a researcher studying cultural history and semiotics. After systematically comparing the referencing and mapping of tattoos by interviewees in St. John‘s, Newfoundland, the author argues that tattoos should be viewed in a light that reflects the endless potential of human self-expression. Part of this statement is meant to address the structure-agency dichotomy which has long been reflected in the literature on sociological theories and the tattooing/body literature. Another part is meant to give substantive evidence to the claim that regardless of motivations or meanings, the truth behind meaning and identity can only be found in complex and ephemeral moments which populate the life of the cultural and individual actor.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.032
Scholarly communication0.0090.011
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.301
Teacher spread0.279 · 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 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

Citations14
Published2013
Admission routes3
Has abstractyes

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