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Record W1689253109

Beyond Downton Abbey: Remembering the Great War's Fallen Through Education and Marketing

2015· article· en· W1689253109 on OpenAlexaboutno aff
Nina M. Ray, Andrew T. Mink

Bibliographic record

VenueDigitalCommons - Kennesaw State University (Kennesaw State University) · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsBattleBattlefieldWorld War IITourismSpanish Civil WarCommissionHistoryDark tourismPolitical scienceMedia studiesAdvertisingSociologyLawArchaeologyAncient historyBusiness
DOInot available

Abstract

fetched live from OpenAlex

This paper explores the expanding marketing and education mission of the American Battle Monuments Commission (AMBC). Superintendents at overseas cemeteries and battle sites must continue their job of “keeping the headstones white and the grass green” but also must market specific events such as the 70th anniversary of D-Day at the Normandy location and an upcoming 100th anniversary of the end of the Great War in 2018. Part if the effort is passing the memory on to the next generation via materials relevant to young people today. U.S. history teachers who received ABMC grants to travel to Meuse-Argonne in France (the resting place of the most U.S. fallen of any overseas cemetery) to prepare material to teach World War I served as one of two samples for empirical data. Another sample was drawn from battlefield tourists who visited the Normandy World War II beaches on the 70th Anniversary of D-Day. Results show “maintaining the memory”, “telling others,” and “simple connection to values/heritage” are key phrases chosen by the respondents on a battlefield tourism survey. From both groups, “I feel proud to visit” was important. “Pilgrimage” is more relevant for the older D-Day group than the younger teachers, but both groups indicated that direct interaction with the veterans who were there (Canadian D-Day vets, or in the case of World War I, the teachers spent time with children of WWI soldiers) were major highlights of the trip. Future research will investigate whether these themes are still important motivators once the era of anniversaries is over.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.193
Teacher spread0.167 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

Explore more

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