Dossier #010 | Attribution Discipline

Selection, consecration, cultivation, and how a university audits what it claims to have grown.

09:00 New York · 14:00 London · 21:00 Beijing

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On 23 July, the day Professor Hong Wang was awarded the Fields Medal, Peking University’s School of Earth and Space Sciences, the school she entered in her first year and later transferred out of, sent a letter of congratulations. It described her as ‘an outstanding representative cultivated by Peking University’ and said that her award was ‘even more a reflection of the quality of Peking University’s cultivation of talent in the foundational disciplines’. On the same day, an official Peking University report said that the spirit of exploration shown by Wang and Yu Deng came from sustained inquiry, experimentation and perseverance, and also from their study and accumulation at Peking University’s School of Mathematical Sciences. This kind of institutional credit is extremely common in public relations and student recruitment. French President Emmanuel Macron likewise wrote on social media that Wang ‘embodies the excellence of our research and our training’ (’elle incarne l’excellence de notre recherche et de notre formation. Fierté.’), adding in English: ‘Choose France for science!’

Yet Peking University’s congratulations prompted a legitimacy dispute in public discussion, with criticism centring on whether the University had the ‘right’ to claim such credit. Peking University did take part in the formation of Wang’s capabilities. What the public was really asking, however, was this: before the world recognised her, did the University allow her to be seen, encouraged and believed in? (See Issue #012.)

Nearly a month later, on 17 August, the Beijing International Center for Mathematical Research published on its WeChat account a ten-thousand-character interview with alumna Hong Wang, containing multiple accounts of her time at Peking University. This provided unusually good material for a before-and-after comparison using the Institutional Cultivation Claim Audit framework, which we were developing at the time. Under this framework, the new interview substantially strengthens the evidence that Peking University made a Bounded contribution to Wang, particularly by filling in what had previously been the least clear and the most important dimension: support for the person. This directly answers the question that concerned the public most.

The wording of Peking University’s earlier public letter, however, still warrants care because it credits this case at the level of System capacity, and that level cannot be supported by the public evidence currently available. A link to the short-form checklist is included in the comments below. It contains three audit dimensions, twelve questions, three levels of institutional credit, and a results table, and uses the Peking University claim to demonstrate the ceiling of what public evidence can support. The full toolkit is published separately on Substack and available to paid subscribers; the link also appears in the comments.

A Blind Spot

At least three mechanisms operate between elite universities and individual outcomes.

The first is selection. Through highly competitive entry, a university admits students who have already demonstrated stronger capabilities and resources. Selection determines whom the university admits and therefore directly affects the student outcomes observed later. These capabilities and qualities existed before entry and cannot be credited to the university’s cultivation.

The second is consecration. Through institutional acts such as admission, classification and the awarding of degrees, a university formally certifies an individual. The qualification thereby becomes institutionalised cultural capital, while the university’s symbolic authority becomes attached to the individual (Bourdieu, 1986; 1996).

The third, cultivation, takes place in the interval between the first two. This is where the university’s teaching, training and other activities genuinely shape student development.

The problem is that the effects produced by the first two mechanisms are often mistaken for the results of the third. Through selectivity, a university admits a group of people already more likely to succeed; through its reputation and alumni network, it further increases their opportunities. When alumni achieve strong outcomes, the university treats those outcomes as evidence of its cultivation capacity, attracting another flow of applicants and resources.

The alumni outcomes observed by a university are jointly formed by selection, consecration, cultivation, students’ own agency and other external circumstances. The risk is that, if the university cannot see how much each factor contributed, the positive feedback loop may allow it to overlook places where its cultivation system could have done better. The stronger the reputation of an elite university, the stronger its students’ own capabilities will generally be; the university’s contribution is therefore more easily obscured by what those students already brought with them, and the conditions for this blind spot arise more readily.

Defining Cultivation, and What Universities Can Measure

This publication understands cultivation as a university’s formative contribution to two intertwined forms of student development.

Disciplinary and professional formation: subject knowledge, research methods, practical capability and professional judgement, for example.

Transferable human capabilities, dispositions and values: critical thinking, originality, agency, self-efficacy, resilience, confidence, curiosity, ethical judgement and choice, collaboration and long-term thinking, for example.

The former appears more amenable to standardised measurement. Universities can already use data across multiple dimensions to present cultivation outcomes, including changes between entry and final grades, completion rates, employment rates, graduates’ average earnings and student evaluations of teaching. The problem is that, although these outcomes reflect students’ circumstances more directly, the strength of their connection to the capabilities the university cultivated, and to how much the university contributed to those outcomes, cannot bear the causal weight placed upon them in practice. To take a straightforward example: when students at an elite university can obtain excellent results through self-study, high completion rates and high average earnings are insufficient conditions for demonstrating strong institutional cultivation capacity, and the proportion of the outcome attributable to the university is also difficult to measure (see ‘Adjacent Tests’ below).

Some elements of the latter category, such as confidence and resilience, are harder still to measure through conventional indicators. University records rarely preserve specific evidence of these forms of cultivation: the tutorial in which a student began to see what suited her and consequently changed to a direction in which her talent could be used more fully; the support and patience of the supervisor through whom a student first acquired academic confidence. Equally valuable data lie in the experiences of students who did not succeed for a time, left the university part-way through, or were never noticed, and understanding those experiences can reveal potential weaknesses in the system. Even where relevant records exist in university archives and data systems, they are dispersed across different systems, for example the reports of student-faculty liaison meetings or the case records of applications for extenuating circumstances. They are perhaps rarely brought together and read as cultivation evidence.

This produces a noteworthy phenomenon: many universities learn what their alumni actually experienced at the institution only after those alumni succeed and are interviewed. Only then do they discover which teachers and which rules genuinely made an important difference. This information often returns to the university many years late. It is usually triggered by an external event and tends to be confined to alumni who have already acquired a measure of influence and are therefore likely to receive media attention, so it also carries sampling error.

Why Now

Two related trends suggest that, for universities, the second kind of cultivation can no longer remain something that has merely been ‘incorporated into teaching and assessment’. It now needs an account of what it has produced.

First, AI and new technologies have made knowledge, feedback and output easier to obtain. Recent official materials from several elite universities show a convergent direction: while incorporating AI into teaching, they are assigning greater strategic weight to judgement and the formation of values. Oxford’s Strategic Plan 2025–2030 commits the university to continuing to champion critical thinking and originality as defining marks of academic excellence, and public statements by the leadership of Tsinghua and Peking University point in a related direction. A committee report published by MIT in August 2026 states the point more directly, locating the most important product of an education not in the grade or the qualification but in the student herself: in how she has grown, in the intellectual maturity she has reached, and in the imagination, insight and judgement she has developed.

At the same time, the purpose of the university after AI has itself become a subject of public renegotiation among university leaders around the world. The theme of this year’s THE World Academic Summit is ‘Knowledge, justice and futures: Universities in the age of intelligence’. According to an announcement by the University of Bristol, President and Vice-Chancellor Professor Evelyn Welch will deliver the opening and closing remarks and speak in four sessions, one of which will consider what universities should ‘preserve, rethink and reinvent’ in the age of AI. Bristol’s own University AI Principles state that teaching and assessment should ‘intentionally focus on the development of human judgement, creativity and critical thinking’.

This publication interprets this convergence as a change in the relative weight of the factors underpinning university legitimacy. As technological progress makes knowledge, guidance and output easier to obtain, the distinctively human value that elite universities can cultivate will have to bear more of that weight. The more a university needs the ‘cultivation’ of these capabilities to explain its value, the more clearly it will need to put the corresponding evidence in order.

Second, employers have always valued these abstract capabilities, and AI is making them still more important. The World Economic Forum’s Future of Jobs Report 2025 finds that analytical thinking remains employers’ top core skill, with seven in ten companies considering it essential, and that resilience, flexibility and agility, creative thinking, and curiosity and lifelong learning are also core skills rising in importance. The OECD’s Skills in the AI Age, published in July 2026, reports that about a quarter of workers across the OECD were exposed to generative AI between 2022 and 2024, exposure meaning that at least a fifth of a job’s tasks can be assisted by AI, and that this share is projected to grow substantially. The complementary skills defined in that report overlap closely with the transferable human capabilities, dispositions and values defined in the previous section. The report also shows that, among vacancies in occupations with high AI exposure, more than half require at least one skill from the social, emotional or digital groups. This increases both the labour-market relevance of these capabilities and employers’ interest in the question of where they came from.

The way employers verify these capabilities is also changing. Companies have begun to use the language of skills-first to describe the talent they want. The OECD’s A Skills-First Labour Market, published in June 2026, observes that employers continue to report talent shortages even as formal educational attainment continues to rise. Formal education and qualifications remain essential foundations for developing and signalling knowledge and skills, but they cannot always capture the full range of skills individuals possess, nor keep pace with rapidly changing skills demand. Combined with the first trend, this raises the standard of proof: universities are also shifting their own value propositions towards abstract capabilities that have traditionally been harder to verify.

When these two trends occur together, universities increasingly need a clear audit: how much have they cultivated their students’ transferable human capabilities, dispositions and values? The earlier a university clarifies the attribution, setting out what exactly it did in the formation of those capabilities, whom that support reached and what level the evidence can sustain, the greater its room for initiative.

Adjacent Tests

This question has generally been broken into neighbouring questions, and countries have already conducted many relevant tests from which much can be learnt. England ran the most extensively documented national experiment on a similar problem. In 2015, HEFCE attempted to measure students’ learning gain, seeking to quantify their development from entry to graduation, and the work was taken over by the Office for Students in 2018. A separate workstream, the National Mixed Methods Learning Gain Project, attempted to measure learning gain through student surveys, but several responding institutions reported that they appeared to average a response rate of 1 to 2 per cent. After interim findings were reported in March 2018, the OfS discontinued administration and evaluation of the questionnaire and replaced it with a more student-centred, qualitative approach to students’ perceptions and conceptualisations of learning gain. The final evaluation of the pilots, published in 2019, concluded that no simple ‘silver bullet’ metric could measure student learning accurately and effectively across subjects of study and institutional types.

After the earlier learning gain pilots failed to identify a common measure, TEF 2023 recast the question as educational gains and divided it into three elements within the student outcomes aspect: a provider’s articulation of the gains it intends its students to achieve; its approach to supporting those gains; and evidence of the gains its students have achieved. The change in name was also a shift in the burden of proof. Learning gain presupposed a measure that the regulator could apply; educational gains returned the authority to define them to the institution. In the absence of a common national measure, the OfS required providers to give their own account and, where possible, to provide evidence of actual achievement, which presented English universities with a non-standardised evidential problem. After the results were released, the QAA analysed a group of providers awarded either an overall Gold rating or a Gold rating for student outcomes. It found that many submissions lacked the ‘golden thread’ that should run from a definition of educational gain through the endpoint intended and the method of measurement to the evidence offered, and that providers could select only positive evidence, sometimes treating league-table rankings or external examiner comments as evidence of gain.

Can students’ evaluations of their teachers demonstrate a university’s cultivation capacity? A meta-analysis by Uttl and his co-authors, covering all available multisection studies, found no significant correlation between student evaluation of teaching ratings and student learning. Those scores therefore cannot bear an inference about how well a teacher teaches. This publication nevertheless considers student accounts, appeals and exit interviews useful for identifying mechanisms, developing causal hypotheses and locating negative cases. They cannot, however, be treated as ratings, nor can they alone demonstrate the prevalence of a particular cultivation practice.

The national regulator in England no longer requires every provider to demonstrate wider educational gains through detailed supplementary submissions. In its final decision of June 2026, the OfS determined that the future TEF would use a more streamlined, data-led assessment of student outcomes, and that providers would no longer be required to submit detailed supplementary evidence of their approaches to delivering positive outcomes or educational gains. The OfS considered the continuation of the previous educational gains approach for every provider excessively burdensome, while the new approach would help to reduce burden and make assessment results more comparable.

Nor has a continuously operating common system emerged internationally. The AHELO feasibility study reached positive conclusions about feasibility, but in 2015 the OECD decided not to pursue the proposed main study after failing to reach consensus, and between 2016 and 2021 a smaller six-country study continued using CLA+. In its 2022 account, the OECD noted that while PISA had become the global benchmark for the learning outcomes of 15-year-olds, there is still no valid and reliable measure of the learning outcomes of higher education students and graduates.

In short, educational gain is becoming more tractable in local, bounded forms at the same moment that it continues to resist uniform national governance.

Another Point of Entry: Audit the Claims

Looking back at these experiments, existing frameworks measure student gain or audit institutional capacity. Our gap is this: we audit the inferential bridge by which a university converts student success into an institutional claim. In other words, we examine how a university manages the credit it takes for student outcomes.

This method approaches the question of how much a university has cultivated from another angle, through a more operational point of entry. Starting with how much the student changed not only creates a problem of common measurement; it also leaves the further question of how much the university contributed to those changes. Auditing what contribution the university claimed, and how much evidence that statement can bear, divides a vast question into many lighter, more readily executable tasks. The reason is that the unit of audit is one specific claim made by the institution itself. It is not necessary, on every occasion, to complete university-wide data collection and a systemic account.

The limitation of this audit method is that it may not cover every aspect of the system, and doing so would itself require sustained investment on a considerable scale. Its advantage is that applying a common logic to each claim made by the university can accomplish the two most important goals: taking credit with evidence, and locating places where the system and its execution can be improved.

Each completed audit can yield new insight and evidence about the institution’s cultivation mechanisms. The university can use those mechanisms to establish an evidence provenance map and update it over time through successive audits. This map can include institutional policies and resources, traces of execution, first-person student materials, differences in reach, failure cases and the governance practices the institution has developed through previous audits.

The most demanding part of the method comes in the first audit, when the institution must determine, in light of its particular circumstances, where each piece of evidence is held and who can provide it. Once that work is complete, the provenance map becomes an institutional asset, and later audits need to return to the relevant department only when a gap appears.

As audits accumulate, four kinds of insight will gradually emerge: forms of cultivation that the institution itself has not noticed but that matter in practice; claims made at a level higher than the evidence can support; claims fully supported by evidence; and capabilities the institution already possesses but has neither noticed nor communicated. Taken together, these four categories can gradually bring the cultivation profile of a university or faculty into view.

The Credits Frame: Three Levels of Institutional Credit

This publication divides institutional credit into three levels: Association, Bounded contribution and System capacity. An audit uses them to make two judgements: the level at which the claim itself takes credit, and the level at which the evidence can sustain it. Whether the two align, and the direction in which they diverge, is the finding of the audit.

Association: the individual studied, researched or worked at the institution, or had another relationship to it that can be stated clearly.

Bounded contribution: the evidence can identify one or more specific mechanisms, for example permission to change programme, a dedicated supervisor, course-based training, a structured peer environment, resources or introductions, and can credibly show that they formed part of the student’s developmental path.

System capacity: the institution can demonstrate that the relevant conditions form a consistent system, supported through resource allocation and cross-departmental execution; that the system is recorded and verifiable; and that it can show differentiated outcomes, including failure and withdrawal. In other words, the support provided to a student by one supervisor or one opportunity cannot by itself establish a systemic institutional capability. System capacity requires a relatively stable mechanism through which relevant students have a reasonable opportunity to obtain such support when similar circumstances arise.

The higher the level of institutional credit claimed, the higher the evidential requirement. Consider Peking University and Hong Wang. An alumna becoming a Fields Medallist can demonstrate an Association between a Fields Medallist and the institution. The University allowed her to transfer from the School of Earth and Space Sciences to the School of Mathematical Sciences and provided undergraduate research, dissertation supervision and a peer-learning environment supported by student-run seminars and an undergraduate reading room. This evidence can support Bounded contribution. Yet the case of one winner cannot by itself demonstrate that Peking University can systematically identify, protect and cultivate unconventional or initially unrecognised mathematical potential. A claim at the level of System capacity can be supported only when this support forms a system, leaves traceable records of execution, gives students in the relevant population a clear and realistically accessible opportunity to obtain it, and can account for the boundaries revealed by failure cases.

The more closely the evidence corresponds to the exact gain being audited, the more strongly it can demonstrate the institution’s contribution to that form of cultivation. Where an institution makes an overarching claim covering several forms of cultivation, each aspect requires corresponding evidence.

The Checklist

On the basis of this analysis, this publication has developed an Institutional Cultivation Claim Audit toolkit. It is intended to strengthen attribution discipline, expose evidential gaps that require further investigation and form an institutional cultivation profile consistent with its stated definition. Universities can use it to test whether claims and actual evidence align. The gaps it reveals in resource allocation or execution can help a university identify weaknesses and blind spots in its system. It can also reveal cultivation strengths that the evidence is sufficient to support but that the university itself has not noticed, converting an undervalued strength into a public claim with a clear evidential boundary. When a university or faculty applies for funding, responds to regulation or participates in rankings, the toolkit can also help it prepare logically rigorous, evidence-supported materials.

The toolkit is published in two parts. To make it easier for audit specialists to learn and use, a Short-Form Checklist is appended to this article. It contains three audit dimensions, twelve specific questions, three levels of institutional credit and a results table, and uses the Peking University claim to demonstrate the ceiling of what public evidence can support. A real audit of Peking University would require internal materials. The checklist is designed for a quick check of a claim already published or about to be published, to determine whether it merits a full audit. Its output is a judgement, not an externally defensible audit conclusion. The Short-Form Checklist is freely available with this article.

Because the content and rules of the toolkit are relatively complex, the full version is published separately, again to make it easier for audit specialists to learn and use. It contains nine worksheets; a list of the evidence required by default for each of the twelve questions; roles and audit costs; a plan for collecting and stratifying student evidence; rules for prioritising evidential gaps; rules for deriving the decision-maker’s summary; and a complete, question-by-question demonstration of the Peking University case. The full version contains the underlying logic for investigation and insight. It is best used with a large language model deployed securely on the university’s local systems, reducing the time required to learn the process and helping to create a clean data asset. The full version is published on Substack and available to paid subscribers; the link appears in the comments.

At present, the framework is a conceptual diagnostic framework grounded in existing research. At the time of publication, it has not undergone multi-institutional piloting, reliability testing or validation. If cases of practical validation become available, they will be added to this article.

Verdict

The dispute surrounding Peking University shows that the once-natural inference from celebrating an alumna’s success to treating it as an outcome of institutional cultivation is becoming harder to take for granted. People are paying closer attention to the university’s real contribution to the development of talent: not only whether it provides high-quality knowledge and resources, but whether it sees the individual; whether every student has a reasonable opportunity to be in an environment where she is supported and encouraged; whether she can develop cognitive capacity, judgement and agency, become someone clear-minded and steadfast, and grow the capacity to support and care for others.

The relationship between an institution and alumni success has levels of increasing depth. Association, Bounded contribution and System capacity are often left undifferentiated in the logic of universities’ public narratives. Peking University can now present two kinds of Bounded contribution evidence: professional training, and support for the person. Its public letter, however, made a claim at the level of System capacity, and the public evidence currently available about Hong Wang cannot support that level. The new interview published on 17 August shows that this crucial kind of evidence does exist, but it appeared late and has not yet formed systemic evidence. The University may already hold these materials internally and simply never have assembled them into traceable cultivation evidence. A failure to distinguish levels of institutional credit, and a failure to see important cultivation evidence in time, were both among the blind spots behind this legitimacy dispute.

The level of institutional credit cannot be raised through public relations and communications. A university can, however, organise its real level of contribution and the corresponding cultivation evidence in advance. This is precisely where the institution itself has the greatest power to see and to change.

Notes

1. 北京大学地球与空间科学学院 (Peking University School of Earth and Space Sciences), 《热烈祝贺我院 2007 级王虹同学获得 2026 年数学菲尔兹奖》 (’Warm Congratulations to Hong Wang of Our 2007 Cohort on Receiving the 2026 Fields Medal’; in Chinese), 23 July 2026.

2. 北京大学新闻网 (Peking University News), 《北大校友王虹、邓煜荣获菲尔兹奖》 (’Peking University Alumni Hong Wang and Yu Deng Awarded Fields Medals’; in Chinese), 23 July 2026.

3. Emmanuel Macron, LinkedIn post, July 2026.

4. Sutong Chen, ‘Issue #012 | The Storm Beneath a Fields Medal’, The Velvet Scalpel, 2026.

5. 北京国际数学研究中心 (Beijing International Center for Mathematical Research), 《从弗斯滕伯格猜想到挂谷猜想｜专访 ICM2026 邀请报告人王虹校友》 (’From the Furstenberg Conjecture to the Kakeya Conjecture: An Interview with Alumna Hong Wang, an Invited Speaker at ICM 2026’; in Chinese), 17 August 2026.

6. Han Yangmei, 《独家专访王虹：从北大数学系曾经的”小透明”，到今天的菲尔兹奖得主》 (’Exclusive Interview with Hong Wang: From an Unnoticed Student in Peking University’s Mathematics Department to a Fields Medallist’; in Chinese), China Science Daily, 24 July 2026.

7. Jiang Jiefeng, Gu Xinghang and Su Shirong, 《特稿｜王的猜想》 (’Special Report: Wang’s Conjecture’; in Chinese), Guangxi Daily, 24 July 2026.

8. Pierre Bourdieu, ‘The Forms of Capital’, in J. G. Richardson (ed.), Handbook of Theory and Research for the Sociology of Education, New York: Greenwood, 1986, pp. 241–58; Pierre Bourdieu, The State Nobility: Elite Schools in the Field of Power, trans. Lauretta C. Clough, Cambridge: Polity Press, 1996.

9. University of Oxford, Strategic Plan 2025–2030, ‘Education and Learning’, Objective 2(d), 2026.

10. 清华大学 (Tsinghua University), 《清华大学校长李路明：推进 AI 开放联盟建设 支撑”人工智能+教育”》 (’Tsinghua University President Li Luming: Advancing the AI Open Alliance to Support “AI + Education”’; in Chinese), 12 April 2026.

11. 《对话北京大学党委书记何光彩｜以数智变革之笔 书写教育强国时代答卷》 (’In Conversation with He Guangcai, Party Secretary of Peking University’; in Chinese), Yujian News interview, during the 2026 World Digital Education Conference, May 2026.

12. Massachusetts Institute of Technology, Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, Report, section 2.4, 13 August 2026.

13. University of Bristol, Our University AI Principles, accessed 2026.

14. University of Bristol, LinkedIn post announcing Professor Evelyn Welch’s participation in the THE World Academic Summit 2026, 24 August 2026, accessed 1 September 2026; Times Higher Education, THE World Academic Summit 2026, Cape Town, 29 September–1 October 2026, accessed 1 September 2026.

15. World Economic Forum, Future of Jobs Report 2025, section 3.1, 2025.

16. OECD, Skills in the AI Age, OECD Artificial Intelligence Papers No. 60, 2026.

17. OECD, A Skills-First Labour Market, Getting Skills Right, 2026, DOI 10.1787/2e1b85f0-en.

18. Camille B. Kandiko Howson, Final Evaluation of the Office for Students Learning Gain Pilot Projects, report to the Office for Students by King’s College London, July 2019, section 1.5.

19. Stella Jones-Devitt et al., Evaluation of the National Mixed Methods Learning Gain Project (NMMLGP) and Student Perceptions of Learning Gain, report to the Office for Students, July 2019, pp. 6, 17.

20. Office for Students, Regulatory Advice 22: Guidance on the Teaching Excellence Framework 2023, 2022, Annex A; Office for Students, ‘Approaches to Identifying and Measuring Educational Gains in TEF 2023’, 4 April 2024; IFF Research, Teaching Excellence Framework 2023: Evaluation Report, report to the Office for Students, February 2025.

21. Quality Assurance Agency for Higher Education, Educational Gain Project Report, ‘Summary of analysis’, report lead Jacqueline Stevenson, project lead Camille Kandiko Howson, June 2024.

22. Bob Uttl, Carmela A. White and Daniela Wong Gonzalez, ‘Meta-analysis of Faculty’s Teaching Effectiveness: Student Evaluation of Teaching Ratings and Student Learning Are Not Related’, Studies in Educational Evaluation, 54, 2017, pp. 22–42.

23. OECD, AHELO Feasibility Study: Progress of Work, EDU/IMHE/AHELO/GNE(2012)6, March 2012; OECD, Does Higher Education Teach Students to Think Critically?, Paris: OECD Publishing, 2022, chapter 1.

24. Office for Students, Future Approach to Quality Regulation: Consultation Outcomes, June 2026, especially paragraphs 114–16, 163, 166, 176–7, 194 and 272.

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Sutong

The Velvet Scalpel