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Record W1978150251 · doi:10.1353/nin.2013.0028

Rooting for the Clothes: The Materialization of Memory in Baseball’s Throwback Uniforms

2013· article· en· W1978150251 on OpenAlexvenueno aff
Stephen Andon

Bibliographic record

VenueNine · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsClothingAdvertisingPsychologyArtBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Excerpt At their essence, sports jerseys function as symbolic materializations that foster a constitutive identity and unity between fans, players, and cities or regions. When new teams are created, often the team logo and uniform are the first manifestations of the team’s identity. These designs are so important that many franchises consult with professional marketing firms on new designs intended to connect with new fans and maximize merchandizing streams.1 Furthermore, when teams acquire new players, the first act as a new member of the team often involves a ceremonial press conference that is opened by the new player donning the team’s jersey (a similar practice takes place during amateur drafts for new players). The jersey thus signifies both an identity and a membership while existing as a transformative object with its own magical provenance: the wearer, whether on the field or off, defers their individual identity for the sake of a team. As such, jerseys are constantly put in place as performance pieces, as when uniforms are raised to arena rafters to give enduring presence to their greatness, or when city statues are draped in team jerseys to unite the citizenry. These uniforms come to symbolize more than just a team; they can become transcendent icons that represent a city, even a country, and its enduring memories.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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Same venueNineSame topicAmerican Sports and LiteratureFrench-language works237,207