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Record W4389967375 · doi:10.14453/asj/v12i2.10

It’s About Us: Extinction, Contradiction, and the Mourning of Modernity in David Attenborough: A Life on Our Planet

2023· article· en· W4389967375 on OpenAlexaff
Alex Ventimilla

Bibliographic record

VenueAnimal studies journal · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsModernitySociologyEnvironmental ethicsAestheticsPopularityAnthropocentrismHistoryArtLawEpistemologyPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Despite their worldwide viewership, popular eco-documentary treatments of biodiversity loss and the ecological grief they evoke have received scarce attention from critics. Addressing this gap in scholarship, this article posits that understanding the grief and mourning affected by these cultural texts requires attention to the numerous contradictions inherent to the form. More concretely, this paper argues that a thorough exploration of the contradictory nature of the eco-documentary, as a media genre that is imbricated in the modernity whose impact on the natural world it critiques, renders the genre into a critical junction at which to interrogate the cultural meanings of the mass extinction of biodiversity. This is done through an analysis of David Attenborough: A Life on Our Planet. This study suggests that popular ecodocumentary representations of biodiversity loss such as this remain entrenched in an anthropocentric instrumentalism characteristic of the modernist paradigm. Acknowledging the unwavering popularity of such films, this study concludes by positing that it is through attentiveness to rather than a wholesale rejection of eco-documentaries like A Life on Our Planet that scholars and viewers alike stand to grasp the extent of the fallacy and the fall of modernity and its worldview.

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 score0.290
Threshold uncertainty score0.472

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 studies0.0010.000
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 head0.051
GPT teacher head0.266
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

Citations0
Published2023
Admission routes1
Has abstractyes

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