Distributive Justice and the Sustainable Development Goals: Delivering Agenda 2030 in India
Bibliographic record
Abstract
Abstract The sustainable development goals (SDGs) present a real opportunity to direct India towards a path of equality and equity. This article posits that India’s plans to achieve the millennium development goals by the end of their term in 2015 faltered because reforms designed to alleviate poverty and achieve equitable growth did not adequately address weaknesses in institutions of accountability, which undermined the reform agenda. These institutions, which include Parliament and the judiciary, exist in part to ensure that actions taken by public officials are subject to oversight so that government initiatives meet their stated objectives. As India shifts its attention to Agenda 2030, its renewed commitment to institutional reforms represents an occasion for the state to address the inequalities in income and the resulting human development concerns. For the government to achieve the SDGs, this article suggests that India must integrate what we refer to as a baseline conception of distributive justice within its plans, which can account for structural barriers to its development arising from ineffective institutions of accountability and provide the poor with a route towards individual empowerment.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".