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By:

Dr. Kishore Paknikar

29 January 2025 at 8:13:00 pm

Who Really Benefits When Varsities Chase the Numbers?

The Ranking Trap - Part 2 As rankings shape academic reputations and institutional priorities, the pursuit of higher positions risks turning a measure of excellence into an end in itself. AI Generated Image The annual university rankings are announced. Some institutions celebrate, others express disappointment, and many begin examining what they must do to improve their position next year. Publicity departments prepare announcements. Administrators study the indicators. Students and parents...

Who Really Benefits When Varsities Chase the Numbers?

The Ranking Trap - Part 2 As rankings shape academic reputations and institutional priorities, the pursuit of higher positions risks turning a measure of excellence into an end in itself. AI Generated Image The annual university rankings are announced. Some institutions celebrate, others express disappointment, and many begin examining what they must do to improve their position next year. Publicity departments prepare announcements. Administrators study the indicators. Students and parents take notice. Governments, funding agencies and potential collaborators may also pay attention. An entire ecosystem responds to the movement of numbers. In the first article of this series, I argued that rankings provide an incomplete picture of educational and scientific excellence. But that raises an equally interesting question. If their limitations are widely recognised, why have they become so influential and who really benefits? The Ranking Economy For some organisations, rankings and research-performance information are commercial activities. QS publishes international university rankings and offers institutional analysis and advisory services. Elsevier supplies bibliometric databases and research analytics used by universities and research organisations. These are different activities, and providing paid services does not, by itself, establish that a ranking or database is unreliable. The more important question concerns the incentives created when institutions become increasingly dependent on numerical comparisons. As universities attach greater importance to their measured performance, demand grows for analytical tools, consultancy, benchmarking and services that help institutions understand and communicate their achievements. But commercial organisations are hardly the only beneficiaries. Universities gain prestige and publicity. Administrators acquire convenient indicators for demonstrating progress. Governments and funding agencies obtain seemingly straightforward comparisons. Students and parents receive simple guidance through a complicated educational landscape. Even the media benefit. A university's rise or fall in a ranking makes an attractive headline. Rankings survive partly because they provide something genuinely useful: simplicity. They compress enormous amounts of information into numbers that are easy to understand and communicate. While their convenience is real, their apparent completeness is not. Peer Pressure Consider what happens when a university announces that it has moved up ten places. The institution publicises the achievement. Prospective students and collaborators notice. Other universities become anxious about their own positions. Administrators study the ranking criteria more closely. Ranking organisations gain further visibility and influence. The process reinforces itself. Universities treat rankings as important because others pay attention to them. Others pay attention because universities treat them as important. Eventually, participation becomes difficult to avoid, even for institutions that recognise the limitations of the system. The influence of rankings therefore does not come solely from those who prepare them. It comes from the authority that universities, governments, funding agencies and society collectively confer upon them. Three words are frequently used as though they mean the same thing: excellence, recognition and reputation. But they do not. Excellence concerns what a scientist or institution actually achieves. Recognition concerns whether those achievements are noticed and acknowledged. Reputation concerns what others believe about their quality. A scientist may produce outstanding work without attracting much attention. An institution may retain a prestigious reputation even when its performance changes. Another may be improving rapidly while remaining relatively unknown. Reputation can outlive the evidence that originally created it. Recognition, meanwhile, may take years to catch up with emerging excellence. Consider the widely publicised Stanford–Elsevier Top 2 percent Scientists lists. A 2026 study in Scientometrics identified 123 universities across 32 countries referring to these lists in official communications. This does not mean that the scientists were undeserving, or that all universities behave similarly. It illustrates how citation-based recognition has become a source of institutional publicity. A researcher may have spent decades producing valuable work without much public acknowledgement. Appearance in a widely publicised list can suddenly generate congratulatory messages, press releases and social media attention. What changed? The scientist's work did not necessarily change overnight. Its visibility did. Recognition is valuable, but we should not confuse the ease of celebrating an achievement with the significance of the achievement itself. Reputation can be converted into opportunity. A prestigious university may attract talented students, accomplished faculty, philanthropic support, research funding and industrial partnerships. These advantages can strengthen its educational and research performance, helping it maintain or improve its position in subsequent rankings. Meanwhile, another institution may have capable teachers and imaginative researchers but inadequate laboratories, limited funding and little national visibility. Rankings need not have created these inequalities. But they can reinforce advantages that already exist. The cycle is straightforward. Achievement attracts recognition. Recognition builds reputation. Reputation attracts resources. Resources create further opportunities for achievement. Rankings can reinforce the entire process. This becomes particularly important when rankings influence public investment. Should scarce research funds go primarily to institutions with proven records, or should some be directed towards institutions capable of achieving much more if given an opportunity? There is no simple answer. Advanced research requires sophisticated facilities and experienced teams. Ignoring established capability would be irresponsible. But concentrating resources indefinitely among successful institutions could prevent promising new centres from emerging. India's Anusandhan National Research Foundation provides an instructive example through its Partnerships for Accelerated Innovation and Research (PAIR) programme. In its first phase, eligibility to lead research networks as hubs was linked to specified NIRF positions. At the same time, the programme deliberately included less-established institutions as partners to strengthen their research capabilities. This is a constructive attempt to combine established capacity with emerging potential. It illustrates a larger policy challenge: rewarding past achievement and creating future opportunity are different objectives, and they need not always rely on identical criteria. Goodhart’s Law Rankings influence not only how institutions are perceived but also how they behave. A university seeking a higher position studies the indicators, identifies where points can be gained and adjusts its priorities. Some changes may genuinely improve teaching, research or infrastructure. Others may primarily improve its score. This is the danger captured by Goodhart’s law: when a measure becomes a target, it may lose its usefulness as a measure. If publication counts dominate evaluation, researchers may feel pressure to publish more frequently. If citations carry excessive weight, fashionable subjects may become more attractive than difficult questions whose significance is uncertain. If reputation is heavily rewarded, publicity may receive disproportionate attention. These outcomes are not inevitable. Indicators can encourage genuine improvement. The problem arises when success on the indicator becomes more important than the purpose it was intended to represent. Competition can improve performance, but science also depends on cooperation, shared facilities and the exchange of ideas. A system that rewards relative position too heavily may weaken incentives to collaborate. Perhaps the most revealing feature of rankings is that even their apparent winners may lose some freedom. A highly ranked university cannot easily disregard the system because its prestige is partly tied to it. Administrators become anxious about annual movements. Researchers celebrated for appearing on citation lists may feel pressure to remain there. Institutions that recognise the weaknesses of rankings may nevertheless continue celebrating favourable results. Refusing to participate can appear more damaging than accepting a system they do not entirely trust. The ranking trap is therefore not simply a story about commercial interests or academic vanity. It is a system of mutually reinforcing incentives that has become difficult to escape. Rankings contain useful information. The problem is the authority we have allowed them to acquire. We created rankings to recognize excellence. We now risk mistaking success in rankings for excellence itself. (The writer is an ANRF Prime Minister Professor at COEP Technological University, Pune, and former Director of the Agharkar Research Institute, Pune. Views personal.)

AI in Sperm Sorting: An Unbiased Decision for A Better Outcome

Nov 7, 2024
3 min read

Artificial Intelligence or AI is revolutionising fertility treatments of the future. The inclusion of AI enhances the accuracy, efficiency, and objectivity of sperm selection, hence potentially improving fertility outcomes by leaps and bounds. Traditionally, sperm sorting through manual methods is subjective to judgments. Processes like centrifugation and swim-up methods are used to separate sperm based on motility and morphology. Although they are effective, they have their limitations, leading to human errors that affect the success rates of fertility treatment. For instance, studies have shown that traditional sperm sorting techniques can have variability in success rates, with reported live birth rates ranging between 15 per cent to 25 per cent per cycle depending on the method and quality of sperm. Hence the introduction of AI helps in maintaining consistency in evaluations of sperm, using the same data set for every sample which leads to better judgments.


Automation and Standardisation- Automation of sperm selection and also introduction of AI in the process have improved the results in ART. AI-assisted sperm selection improves the accuracy in choosing high-quality sperm for fertilisation purposes, and also, pregnancy and live birth rates might be improved. Technologies like Intracytoplasmic Morphologically Selected Sperm Injection along with AI ensure the chances of pregnancies increase by about 10-20 per cent compared to the standard procedures. AI and Automation will decrease time taken to analyze sperm and increase opportunities to select better sperm with DNA integrity for better development and higher success rates in embryo selection. These processes ensure that the sperm selection process follows consistent criteria, reducing variability in outcomes caused by human error.


Analysing Complex Data for Better Outcomes- AI plays a crucial in improving IVF outcomes by analysing complex data and providing tailored recommendations. AI-driven tools and models such as those on SpOvum.ai point towards an opportunity to optimise ovarian stimulation decisions by assessing patient characteristics and follicle growth patterns. A study revealed that the use of AI in IVF improved egg yield and reduced medication costs. AI enables fertility specialists to make data-driven choices, improving overall IVF success rates and streamlining treatment processes.


Reducing Human Error- AI models can continuously learn and refine their performance by being trained on newer data. This adaptability ensures the technology remains unbiased and up-to-date with the latest scientific insights into sperm quality and fertility success rates. Studies have shown that AI-driven sperm sorting can decrease human-related errors by up to 25 per cent, improving sperm selection quality in terms of morphology and motility.


Reduction of Sperm Damage- The new AI-driven sperm sorting techniques also include microfluidic systems that are known to exhibit several advantages over the most commonly used conventional method, which is centrifugation. Traditional centrifugation methods, such as density gradient centrifugation, also cause severe oxidative stress and DNA fragmentation of the sperm because of the very high mechanical forces involved. The AI-infused microfluidic sorting minimises this damage significantly by involving gentler processes that mimic the natural pathway of sperm selection. The studies show that the process of microfluidic sorting decreases DNA fragmentation in sperm, which gives improved opportunities for success for IVF. For example, DNA fragmentation is 20 percent lower in sperm sorted using microfluidic processes than in traditional processing methods.


AI is bound to play an increasingly definitive role in fertility treatments, which will improve the outcomes for couples experiencing infertility.


(The author is a Co-Founder & CEO at SpOvum® Technologies. Views personal.)

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