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Record W2940635598 · doi:10.1080/17449626.2019.1601820

An Indian global ethics initiative

2019· article· en· W2940635598 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

VenueJournal of Global Ethics · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsCarleton University
Fundersnot available
KeywordsPolitical scienceSociologyEnvironmental ethicsLawPublic administrationEngineering ethicsPhilosophyEngineering

Abstract

fetched live from OpenAlex

In what sense must global ethics be global? In one sense, it must deal with global issues. In another, it must not be parochial but inclusive of normative views from around the world. So far, global ethics has met the first standard much better than the second. Authors based in the global South contribute approximately 5% of the internationally published research on global ethics. With this in mind, the co-editors of this special issue sought to bring more perspectives, experiences, and authors from India into the international global ethics conversation, and so they launched the Indian Global Ethics Initiative. Their first step, this special issue, presents Indian experience and authors on topics including urban development, care ethics, women’s empowerment, fair trade, distorted policy research, poverty, and health. Much of this work is grounded by the authors’ experience in policy-making and advocacy for social and global justice. The co-editors invite contact from interested readers who would like to join and continue this Indian Global Ethics Initiative, as well as readers who would like to take similar initiatives in other regions.

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)0.008
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.005
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 head0.124
GPT teacher head0.449
Teacher spread0.324 · 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