India ranks high in scientific output but lags in research impact. Analyse the causes and suggest measures to improve research quality.

India produces a large volume of research papers. But its citation impact and its share of highly cited work have not kept pace, as DST-CPR's scientometric study of 2014–2023 tracks [1]. The problem is not a lack of talent. It lies in how research is funded, incentivised and judged.

Causes of the output–impact gap

• Incentives built on metrics (Goodhart's Law): hiring, promotion and rankings reward the number of papers and citations. The OECD finds that such narrow metrics create perverse incentives [3], such as splitting one study into many papers, self-citation and citation cartels.
• Low funding: GERD (gross expenditure on R&D) remains below 1% of GDP [2]. Long-gestation fundamental research and quality infrastructure get too little money.
• Official push for more papers: ANRF's June 2026 portal trains researchers in paper-writing and patent filing [5]. This helps, but if success is measured in paper counts, quantity will outrun originality.
• Predatory journals: pressure to publish pushes work into journals with weak peer review. Paper counts rise but citations do not.
• Structural bias: citation databases mainly index English-language journals. Indian-language scholarship, fields with fewer citations (agriculture, humanities) and state universities get too little recognition.

Measures to improve research quality

• Responsible assessment: adopt DORA principles, which judge research by its content, not by journal metrics. UNESCO links DORA to its Recommendation on Open Science [4].
• ANRF grant reform: ask applicants for a few best papers with a short note on what each contributed. Expert review should lead, with metrics only in support.
• UGC/NIRF: treat bibliometric lists as one input, never a pass/fail filter. As the OECD urges, cut low-value evaluation to reduce assessment fatigue [3].
• Credit for Indian languages: SARAL AI translates research into 18 Indian languages for outreach [6]. Evaluation should also count original work published in these languages, in line with NEP 2020's language goals.
• Deeper funding: raise GERD, attract more private R&D and protect basic research.
• National evidence: base policy on DST's own scientometric data [1], not commercial leaderboards.

India's task is to turn scale into significance. Judging contributions instead of counting papers would let research serve both frontier science and national needs. DORA-aligned evaluation, steadier funding and recognition of Indian-language scholarship would get there, and would realise NEP 2020's vision of research-intensive universities.