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Record W4388328168 · doi:10.1525/gp.2023.89122

Heritage and Cultural Affiliation: Archaeological Materials in the Performance of Identity and Belonging in Igbo Ukwu, Southeastern Nigeria

2023· article· en· W4388328168 on OpenAlexaff
Elizabeth Adeyemo, Ugochukwu Okoye

Bibliographic record

VenueGlobal Perspectives · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsCarleton University
Fundersnot available
KeywordsIgboMateriality (auditing)Representation (politics)Identity (music)SituatedArchaeologyAnthropologyNarrativeSociologyHistoryAestheticsIdeologyLinguisticsArtLiteraturePoliticsPhilosophyLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This paper explores the use of images of archaeological objects as a conduit for members of a social group to establish a connection with the past, shape new realities of identity, and express a sense of belonging. With a focus on Igbo Ukwu, a renowned archaeological community in southeastern Nigeria, this paper follows the discourse on images as realistic claims to truth situated within heritage studies. Specifically, we conceptualize archaeological objects as a materiality of belonging, examining how their affect among community members extends beyond the tangible objects to include images of the objects reproduced across different media. By examining the elevation of images of archaeological objects to index cultural affiliation between the past and the present, we highlight the emergence and (re)production of corporate notions of belonging in Igbo Ukwu community. This paper contributes to discourse on a holistic approach to the use of archaeological objects in the (re)construction of identities and ideologies. We argue that by tracing the history of representation and the role that images play in it, we are able to isolate and reconstruct the process through which new, or reimagined, realities emerge.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.357

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 communication0.0000.001
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 head0.062
GPT teacher head0.277
Teacher spread0.215 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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