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Record W1983847035 · doi:10.1353/gpr.2014.0003

Junk Jaunt Geography: Buying and Selling America’s Cultural Past in Central Nebraska

2014· article· en· W1983847035 on OpenAlexaboutno aff
H. Jason Combs, Paul Burger

Bibliographic record

VenueGreat Plains research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsTourismAdvertisingPower (physics)GeographyDistribution (mathematics)MarketingSociologyMedia studiesArchaeologyBusiness

Abstract

fetched live from OpenAlex

This project builds on previous material culture research by providing a detailed examination of material diffusion at central Nebraska’s Junk Jaunt. What began in 2003 and is now in its 10th year, the Junk Jaunt annually attracts some 20,000 participants from across the United States and Canada. This article briefly defines material culture and reviews several traditional distribution methods—auctions, the Internet, and garage sales. It also introduces Nebraska’s Junk Jaunt as an example of the growing phenomenon of place-based antiques tourism as communities capitalize on local culture and sense of place. Junk Jaunt organizers provided multiple datasets including participant surveys, guest book registrations, vendor information, and sales of shopper guides. These data illustrate the immense drawing power of Nebraska’s perception as an authentic place, which is reflected in its material culture.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.382

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 studies0.0080.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.049
GPT teacher head0.293
Teacher spread0.243 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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