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Record W2910682754 · doi:10.1080/21550085.2018.1562530

Two Concepts of Wrongful Harm: A Response

2018· article· en· W2910682754 on OpenAlex

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.

Bibliographic record

VenueEthics Policy & Environment · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsYork University
Fundersnot available
KeywordsHarmPoliticsVulnerability (computing)SociologyLaw and economicsEnvironmental ethicsEpistemologyPolitical scienceLawComputer scienceComputer securityPhilosophy

Abstract

fetched live from OpenAlex

As the window of opportunity to limit global average warming to 1.5 °C above pre-industrial levels is narrowing, the impacts of climate change are already being experienced around the world. No longer of merely theoretical interest, the issue of ‘loss and damage’ has become central to climate politics. Against this backdrop, old concepts of responsibility and wrongful harm are being revisited. Boran (2017) proposed moving away from an interactional conception of harm to an architectural one. The former supports the widely shared view that wrongful harm results from actions. The latter turns the spotlight on complexity and social practices. In response to critical appraisals, this short essay revisits key components of an architectural conception of harm. An architectural approach is not an analytic tool to answer the epistemic challenges in singling out those who are causally responsible as a discrete problem. It is an encompassing theoretical framework drawing a picture of a world where vulnerability is inseparably tied to a complex web of social, political, and institutional interrelations. Wrongful harm resulting from climate impacts is inextricable from the constructed environment and everyday practices forming a complex web of social and political interconnections.

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)0.023
metaresearch head score (Gemma)0.039
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.009
Insufficient payload (model declined to judge)0.0050.005

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 head0.193
GPT teacher head0.586
Teacher spread0.392 · 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