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Record W2585319828 · doi:10.31542/j.ecj.878

The Technological Abyss: Heideggerian Ontology and Climate Change

2016· article· en· W2585319828 on OpenAlex
Aaron Mazo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEarth Common Journal · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace Science and Extraterrestrial Life
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsIntelligibility (philosophy)EpistemologyPoliticsAsideClimate changeEnvironmental ethicsSociologySocial psychologyAestheticsPsychologyPolitical sciencePhilosophyLawLinguisticsEcology

Abstract

fetched live from OpenAlex


 
 Whenever a decision is made in a social, political, or economic context, it is implicitly grounded in
 an ethical outlook. But where do these outlooks come from? To investigate this query, I examine
 the basis for ethical decisions regarding technology, focusing specifically on geoengineering
 responses to climate change. Subsequently, I argue that ethical considerations concerning climate
 change, and their corresponding practical decisions, cannot be reliably made without sufficient
 intelligibility regarding the objects and entities these decisions pertain to. To achieve this, I employ
 a Heideggerian phenomenological framework through which being affords intelligibility. Doing so
 elucidates fundamental inconsistencies in the way humans interact with technology. We are caught
 up in what Heidegger calls enframing, the representation of beings as energy reserves. This is the
 ground on which our ethical claims are based, but representation cannot afford actuality. When
 things are represented in this way, truth is set aside in favour of will, and intelligibility is lost. The
 goal, then—if we wish our ethical decisions to be legitimate—must be to gain intelligibility. We
 must therefore free ourselves from enframing and look toward being. We cannot, as Heidegger
 says, affect enframing’s removal, but we can prepare ourselves for such a change. Only once this
 change occurs, can our relationship to technology be intelligible.
 
 
 
 
 
 

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.402

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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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