How expertise is rebuilt across systems and why institutions struggle to recognise it

During a conversation about international football and the FIFA 2026 World Cup with colleagues at work, I found myself thinking about something sport makes unusually visible.

A player can wear the shirt of one country while carrying the training, instincts, discipline, and early formation of another. The team is official. The biography is more complex.

In sport, this is not a problem. It is part of the game.

The player enters the field. Contribution becomes visible. Origin does not disappear, but it is not treated as a contradiction. It becomes part of how the player learned to play.

In research, healthcare, and institutional life, the same movement exists. But it is harder to see.

Professionals trained in one country often work in another. They learn new systems, new languages, new rules, and new silences. They adapt. They requalify. They become legible to a host institution. At the same time, they carry the face of the country that formed them.

Their expertise does not simply move. It is rebuilt.

And this is where institutions often fail. They know how to count credentials. They know how to process contracts. They know how to place people inside categories. They are less able to recognise what happens when a professional is formed by one system and asked to perform inside another.

That failure is not only personal. It is structural.

The problem with visible performance

Sport has one advantage over institutions: it exposes performance. Not perfectly. Not without politics. But visibly enough that fiction has limits. A player may be celebrated, doubted, bought, sold, or criticised. But at some point, the field interrupts the narrative.

Institutions have more hiding places.

In research and healthcare, performance is filtered through proxies: publications, grants, titles, compliance, hierarchy. These indicators matter. They also distort. They record output more easily than contribution. They capture the person who signs, presents, or leads more clearly than the person who stabilises the system.

The result is a strange institutional blindness. Some work is central but barely visible. Some visibility is mistaken for work.

Science knows this problem well. It still likes the myth of the individual genius. The name remains. The laboratory fades. The person who speaks about the work can become more legible than the people who made the work possible.

Bernard Lemaitre describes this distortion as a tension between scientific substance and narcissistic visibility: the work of accuracy, verification, and patience versus the work of persuasion, self-positioning, and institutional influence [1]. The two are not always separate. But when systems reward persuasion more reliably than substance, the balance shifts.

The meticulous become infrastructure. Visibility becomes history.

Learning again to be an expert

When I moved from Ukraine to Germany in 2006 and then followed my career path to Switzerland, I thought I was prepared for an international scientific career. I spoke German and English. I had already worked in scientific environments.

Then I arrived in the canton of Vaud. Daily life was in French. Administration was in French. Housing, banks, contracts, offices — all of it required not only language, but knowledge of a system I had never been taught.

I quickly met what I later called an administrative circle. To rent an apartment, I needed proof of salary.
To receive salary, I needed a bank account.
To open a bank account, I needed an address.
To have an address, I needed an apartment.

On paper, I had a scientific position. In practice, the system assumed I already knew how to enter it.

The solution did not come from official instructions. It came from people. Colleagues, professors, international researchers. Small explanations. Informal knowledge. The kind of information that never appears in the brochure but decides whether a life can begin. One crucial element was the role of a guarantor: someone already established who could reassure a landlord or bank. Often it was a formality. Without knowing it, the circle remained closed.

That was my first lesson in institutions.

Rules rarely explain the system. They often protect those who already know how it works. For a migrant professional, this is not an inconvenience. It is the second training.

The second formation

Migration is usually described as movement. Professionally, it is more than that.

It is a second formation. The expert must learn again how to be recognised as an expert. A diploma may be valid but not fully understood. Experience may be respected but still discounted. Confidence may exist internally, while legitimacy must be rebuilt externally.

This is exhausting. It is also productive. People who cross systems learn to notice what insiders no longer see. They compare procedures, hierarchies, codes, and assumptions. They become sensitive to the gap between formal structure and lived practice.

That sensitivity is expertise.

Yet institutions rarely name it as such. They ask migrants to integrate. They ask them to adapt. They rarely ask what the host system could learn from the person who has already survived another one.

The migrant expert becomes useful before becoming fully visible.

The research precariat

Research offers a sharp version of this pattern.

Nature’s surveys of postdoctoral researchers describe instability, long working hours, uncertain career prospects, low pay, weak support, and limited preparation for careers beyond academia [4–6]. The phrase “research precariat” is not rhetorical decoration. It names a structural condition.

Postdocs produce much of the daily work of science. They run experiments, coordinate data, write protocols, repair methods, train others, and absorb uncertainty. Yet they remain transitional by design.

For internationally mobile postdocs and researchers, the instability doubles. They are temporary in career stage and temporary in migration status. They are forming a scientific identity while translating a social one.

The system benefits from their work before it offers them a stable place.

This is not accidental. It is how many research systems currently function.

The shadow workforce

Every institution has a shadow workforce.

In science, it includes postdocs, technicians, clinical coordinators, research nurses, data managers, and internationally mobile specialists. In healthcare, it includes those who keep care pathways functioning when official pathways are incomplete. In innovation, it includes those who translate between public credibility and private speed.

They do not always appear in the final story.

But remove them, and the system weakens.

This matters because scientific reliability is not produced by ideas alone. It is produced by conditions: time, verification, supervision, stability, and the ability to correct errors. A retrospective analysis of publications in a life-sciences field has pointed to patterns of irreproducibility that raise questions about how research systems produce and validate knowledge [2].

If the people closest to the data are structurally invisible, the system loses part of its capacity to self-correct.

Migration as a stress test

Migration reveals what institutions assume.

It shows whether a system can recognise knowledge that arrives in an unfamiliar form. It shows whether credentials are translated or merely processed. It shows whether diversity is treated as a resource or as an administrative complication.

The OECD reports that foreign-born people now exceed 160 million across OECD countries and that migrant professionals are structurally important in sectors such as healthcare [3]. Yet immigrants continue to face significant earnings gaps, much of which is linked not only to skill but to where they are placed in the labour market [3].

This is the administrative circle at scale.

The problem is not only whether people are qualified. It is whether systems know how to use the qualifications they receive.

A system can depend on migrant expertise and still fail to recognise it.

That contradiction is becoming expensive.

Teams as regulatory systems

As a neuroscientist, I do not see a team as a collection of individuals. I see it as a regulatory system.

Communication is signal transmission. Leadership modulates flow. Trust sets the threshold for whether signals move or are suppressed. Conflict can clarify information or become noise.

Under stress, individual self-regulation becomes depleted. Then collective regulation becomes decisive.

Sport shows this clearly. A team under pressure either fragments or reorganises. Players cover for one another. They adjust. They restore rhythm.

Institutions do the same, but less visibly.

They measure productivity, compliance, and outputs — but not recovery. Whether a team can stabilise after error. Whether people speak early enough. Whether leadership reduces noise or multiplies it. Whether trust exists before crisis arrives.

Yet these features decide whether a system survives pressure.

Public rules, private speed

My own career later placed me between public institutions and private innovation.

Public institutions protect fairness, stability, and ethical boundaries. In science and healthcare, this matters. But public systems also move through documents, job descriptions, committees, and procedures that often lag behind reality.

Private innovation moves differently. It values speed, applied expertise, and practical solutions. That speed can be useful. It can also be dangerous without scientific discipline.

Neither system is pure. Neither is sufficient alone.

Difficult work happens between them.

A clinical innovation can look like progress in one system and risk in another. A collaboration can look necessary to patients and complicated to administration. A job description can regulate work that has already changed.

Operating between systems requires more than expertise. It requires institutional literacy: knowing when rules protect, when they obstruct, and when negotiation is not disobedience but repair.

Crisis knowledge

Ukraine has made this question sharper.

War forces systems to learn brutally. Clinicians, psychologists, rehabilitation specialists, researchers, and organisers adapt under conditions no institution would choose. They coordinate with limited resources. They treat physical and psychological trauma under pressure. They build temporary systems because permanent ones have been damaged.

This knowledge is painful in origin. It is also real. High-resource systems often export expertise to countries in crisis. They are less trained to import knowledge from them.

That asymmetry is a mistake.

Healthcare and research systems across Europe now face budget constraints, workforce shortages, ageing populations, and technological disruption. The ability to optimise without abundance is no longer a peripheral skill. It is becoming central.

Ukraine is not only a place receiving help.
It is also a place producing system intelligence.

What institutions still do not see

The future will not belong only to those who fit one system perfectly.

It will belong to those who can move between systems without losing what formed them. Those who translate. Those who notice friction before it becomes failure. Those who understand that formal rules and informal practice are never the same thing.

This is why the sport analogy matters.

The migrant player is visible because the field exposes contribution. The migrant expert is harder to see because institutions can survive for a long time while misreading the people who sustain them.

But not forever.

Artificial intelligence may soon make work more measurable. It may also make bad measurement more powerful. If institutions continue to count only what already looks familiar, they will automate old blindness.

The deeper question is no longer whether migrant experts can adapt.
They already have.

The question is whether institutions still recognise what expertise has become. Because what migration reveals is not only movement across systems.
It reveals that expertise is no longer formed within a single one.

And institutions that continue to recognise only what looks familiar will not simply exclude people.

They will fail to recognise the very form that expertise is taking.