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Record W4296857922 · doi:10.1016/j.esr.2022.100968

Green transformation in the iron and steel industry in India: Rethinking patterns of innovation

2022· article· en· W4296857922 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

VenueEnergy Strategy Reviews · 2022
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsCarleton University
Fundersnot available
KeywordsTransformative learningAcknowledgementGovernment (linguistics)BusinessIndustrial organizationProduction (economics)Economic systemEconomicsSociology

Abstract

fetched live from OpenAlex

There is growing acknowledgement that industrial processes including the production of iron and steel are a pivotal area ripe for technological change if we are to effectively decarbonize, while concurrently industrialize countries of the Global South in a sustainable way. Innovation is an important element in advancing green (decarbonizing and reducing the environmental footprint) steel production. A narrow view of green steel production points to incremental changes that reduce carbon and other environmental footprints. However, insights from innovation systems and transformative innovation policy highlight the role of directionality of decarbonization pathways, arguing that greening steel will not come about without industrial transformation. This requires an overarching, systematic approach that broadens innovation to effectively transform industry towards decarbonization. Public policies provide mechanisms through which to realize these changes. We turn to the production of steel by large firms in India to ask: what technological innovation efforts are underway? What about the role of technology and innovation cooperation? Regarding the directionality of these pathways, to what extent could these efforts lead to green transformation of the production of steel in India? Drawing from interviews with informants with knowledge of this sector, and various government and industry documents, we found that there is a disconnect between what steel majors and government actors are doing in India – pursuing various activities and policies but doing so in a piecemeal fashion and not pivoting enough towards net zero - and the systemic approach that scholars indicate is fundamental to effectively green the steel sector. Secondly, in contrast to studies that argue that the bulk of international technology cooperation initiatives on R&D are led by the public sector, with the private sector becoming involved at latter stages, various Indian steel majors are actively working on international technology cooperation on R&D. Frontrunner India steel firms are taking proactive steps to produce their steel more sustainably. However, current efforts - principally led by the private sector and where the market for green steel is basically non-existent - to make the sector more sustainable are inadequate. We suggest that governments must play a larger role in promoting innovation to realize the green transformation of steel production in India. International collaboration and technology diffusion combined with national government efforts, which allow for the ‘opening up’ of innovation policy, have the potential to catalyze such systemic changes.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.255
Teacher spread0.222 · 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