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Record W3029795531 · doi:10.3390/heritage3020025

Making Space for Heritage: Collaboration, Sustainability, and Education in a Creole Community Archaeology Museum in Northern Belize

2020· article· en· W3029795531 on OpenAlexfundno aff
Eleanor Harrison‐Buck, Sara Clarke-Vivier

Bibliographic record

VenueHeritage · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory HealthAlphawood Foundation
KeywordsMayaCreole languageArchaeologyGeographyAnthropologyHistoryEthnologySociology

Abstract

fetched live from OpenAlex

Working with local partners, we developed an archaeology museum in the Creole community of Crooked Tree in the Maya lowlands of northern Belize. This community museum presents the deep history of human–environment interaction in the lower Belize River Watershed, which includes a wealth of ancient Maya sites and, as the birthplace of Creole culture, a rich repository of historical archaeology and oral history. The Creole are descendants of Europeans and enslaved Africans brought to Belize—a former British colony—for logging in the colonial period. Belizean history in schools focuses heavily on the ancient Maya, which is well documented archaeologically, but Creole history and culture remain largely undocumented and make up only a small component of the social studies curriculum. The development of a community archaeology museum in Crooked Tree aims to address this blind spot. We discuss how cultural sustainability, collaborative partnerships, and the role of education have shaped this heritage-oriented project. Working with local teachers, we produced exhibit content that augments the national social studies curriculum. Archaeology and museum education offer object-based learning geared for school-age children and provide a powerful means of promoting cultural vitality, and a more inclusive consideration of Belizean history and cultural heritage practices and perspectives.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.669

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.087
GPT teacher head0.301
Teacher spread0.214 · 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.

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

Citations12
Published2020
Admission routes1
Has abstractyes

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