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Record W2790704979 · doi:10.1111/cura.12248

Memories of Manga: Impact and Nostalgic Recollections of Visiting a Manga Museum

2017· article· en· W2790704979 on OpenAlexfundno aff
David P. Anderson, Hiroyuki Shimizu, Shota Iwasaki

Bibliographic record

VenueCurator The Museum Journal · 2017
Typearticle
Languageen
FieldPsychology
TopicNostalgia and Consumer Behavior
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceSocial Sciences and Humanities Research Council of Canada
KeywordsAnimeReading (process)Identity (music)Power (physics)PsychologyArtHistoryAestheticsComputer scienceLinguistics

Abstract

fetched live from OpenAlex

Abstract This study investigated the impact of a visit to a Manga museum in Japan through nostalgic recollections. Twenty‐five adult visitors were interviewed about their childhood memories of experiencing manga from reading books as well as watching anime on television following a visit to the Osamu Tezuka Manga Museum in Takarazuka, Japan. From 76 episodic and autobiographical memories, five themes of impact emerged which speak powerfully to the significant influence and power of Osamu Tezuka's manga and anime on the visitors’ lives as children, and of the power of the museum experience to unlock distant latent memories and reconnect with their own sense of self‐identity. Moreover, the visitors’ own testimony of the impact of manga continued to manifest positively in their lives to the present day as life lessons of enjoyment, morality, and intergenerational learning.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.396
Teacher spread0.355 · 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 designObservational
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

Citations4
Published2017
Admission routes1
Has abstractyes

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