When a measure becomes a target, it ceases to be a good measure. Discuss with reference to research assessment in Indian higher education.

Goodhart's Law says that once an indicator is used to reward people, they work to raise the indicator instead of the quality it was meant to capture. Indian higher education increasingly shows this. Citation counts and inclusion in lists like the "top 2% scientists' database" are treated as proof of excellence, not as one signal among many.

Why metrics are a useful measure

• Objectivity: public citation data applies equally to everyone. It checks patronage and seniority bias in peer review.
• National monitoring: DST-CPR's scientometric study tracks India's STEM output and citation impact for 2014–2023, informing policy [1].

How the measure becomes a target

• Career incentives: when hiring, promotion and institutional rankings depend on citations, researchers chase volume. This encourages self-citation, citation cartels and honorary authorship.
• Publication push: ANRF's 2026 portal trains researchers in paper writing and patent filing [2]. This is useful, but counting outputs alone rewards quantity over quality.
• Distorted priorities: the OECD notes that narrow metrics like impact factors and citation counts undervalue collaboration, openness and societal impact [3]. Long-gestation fundamental research and locally relevant work (agriculture, public health) lose out.
• Linguistic exclusion: ANRF's SARAL AI turns research into content in 18 Indian languages for outreach [4]. Yet original Indian-language scholarship earns little credit in evaluation, which conflicts with NEP 2020's multilingual vision [5].
• Disciplinary bias: the humanities, field sciences and under-resourced state universities have lower citation rates, so they are structurally disadvantaged.

Way forward: metrics as input, not verdict

• DORA principles: judge research on its content, not on journal-based numbers. UNESCO lists DORA under aligning incentives for open science [6].
• ANRF grants: ask applicants for a few best outputs, with a note on what each one contributed.
• UGC and university promotions: treat list membership as information, never a pass/fail filter.
• Indian evidence: rely on DST-type national studies that can be designed to include Indian-language work [1].

Metrics are useful servants but poor masters. The problem is not measuring research but making the measurement the goal. NEP 2020 envisions research-intensive universities [5]. Combining responsible bibliometrics with expert peer review can move India from publication volume to genuine impact, advancing SDG 4 and SDG 9.