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Record W4388705158 · doi:10.3389/frsut.2023.1247407

Be like a panda: reconstructing national identities through China's iconic species

2023· article· en· W4388705158 on OpenAlexaff
Yulei Guo, David A. Fennell, Sam Fennell

Bibliographic record

VenueFrontiers in Sustainable Tourism · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsBrock University
Fundersnot available
KeywordsChinaTourismAppealOrientalismColonialismHistoryGenealogyEthnologyGeographyPolitical scienceArchaeologyLaw

Abstract

fetched live from OpenAlex

Despite lacking clear historical significance, the appeal pandas have to the people of China has played an integral role in the emergence of the country's cultural identity and ideals. Few studies have explored the giant panda due to the ongoing dialogue between the West and China, which, according to Edward Said, is permeated with imperialist, colonial, and orientalist flavors. In 1869, the French missionary Armand David encountered a dead specimen of a giant panda in Baoxing, Sichuan, which sparked the beginning of this dialogue. David shipped the skin to Paris, where the animal was named and aesthetically recreated for the first time for Western audiences. In this paper, we approach the giant panda as a dark tourism attraction embodying a process of making and remaking Chinese national identities over the past two centuries. Using “virtual curating” to study the Giant Panda Museum located at the Chengdu Research Base of Giant Panda Breeding, we demonstrate that the giant panda, which has achieved iconic status in China, represents a national history that is dark, backward, and based on suffering and death. We argue that understanding the giant panda's history as a dark tourism attraction provides an ethical vantage point from which to perceive tourist-panda relationships.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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 score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.303
Teacher spread0.279 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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