Pathways for the Indian steel sector: Realizing low carbon industrial clusters through a place-based approach in eastern India
Bibliographic record
Abstract
There is an increasing realization that current methods to produce materials which underpin modern society such as steel are unsustainable, a challenge particularly acute in India, a rapidly growing economy. However, amidst growing calls for ‘just transitions’ and the need to use a ‘place-based’ approach, conventional strategies for decarbonization that emphasize the adoption of frontier technologies by the steel majors may not be as applicable for certain industrial clusters in India such as those with many smaller firms. So how can industrial clusters in India embark upon sustainability pathways including decarbonization in a just, equitable way? To what extent do history, place-based identity, local socio-economic dynamics and public policy play a role and how? Through document analysis and field research in two steel clusters in eastern India, the most prominent topic discussed by informants was around local socio-economic dynamics, followed by public policies supporting people and place-based identity, and then history. This reiterates the need for pathways to decarbonize clusters to emphasize the local. Furthermore, place-based themes were more pronounced in Giridih, suggesting that for certain clusters placed-based factors may play a stronger role in their potential to decarbonize. Specifically, we found that history influenced variation in workers' wellbeing by firms and awareness of rights and existence of social programs from government. Place attachment existed to both sacred places around the cluster and the cluster itself in Giridih), Place-based identity related to the cluster (steel, coal) and their surroundings (in Giridih to sacred places nearby) was also important. Local socio-economic dynamics helped explain which actors were deemed most legitimate: local elites in Giridih; central and state government in Durgapur such as the Steel Authority of India Limited (SAIL). Policies affecting people (social) such as workers' benefits varied depending on the cluster. These insights can help to develop appropriate decarbonization pathways within respective clusters; ones in which people and places are at the core.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".