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Record W4391987072 · doi:10.7202/1109626ar

The Great Forgetting

2024· article· en· W4391987072 on OpenAlexvenueno aff
Gus diZerega

Bibliographic record

VenueThe Trumpeter · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
Fundersnot available
KeywordsForgettingPsychologyCognitive psychology

Abstract

fetched live from OpenAlex

Why did the modern world enter into a “great forgetting” about the more-than-human world so many indigenous peoples took for granted? Second, how can this previous knowledge be reacquired without rejecting the very real accomplishments of the modern mentality? Many deep ecological writers have done extraordinary work on this second question. I will focus on the first, and use its analysis to add some insights regarding the second. Central to the argument I will make is how language both empowers us and to some degree separates us from direct experience of the other-than-human world. Western languages are particularly prone to reinforcing this separation. Equally central will be a discussion of how media of communication rooted in language further distances us from direct encounter. Also important will be work in contemporary biology and ecology exploring how deeply interconnected all life forms are. The traditional Western idea of individuals, be they plants and animals or human beings, are ultimately irreducibly distinct from their environment has been shown to be mistaken. Individuals have been shown to be made up of simpler individuals who, in relationship with one another, enable emergent qualities to arise at ever greater levels of complexity. Further, while genuinely individual, they cannot be understood without reference to relationships outside what are normally considered individual boundaries. By seeking the foundations of morality and other values in theology, reason, or will, many moderns are blinded to the fact values supporting morality and beauty exist immanently within the natural world. There is no need to import them from elsewhere. By way of conclusion, I reverse direction and describe one method available to the reader how a ‘remembering’ can come about experientially. This remembering will reconnect with an indigenous and sometimes shamanic perception of the world as alive and connected.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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