There seem to be (at least) two fundamentally different ways to approach a career in science. Likely also outside of it. Most people, I guess, recognize both.

One is strategic. You choose labs with strong reputations. You aim for specific journals. You plan fellowships, awards, and timelines. You learn how the system works and try to move through it „efficiently“. Success, in this model, appears visible and measurable. It can be ranked, compared, scored. But that clarity is, at least in part, an illusion. It filters out many excellent scientists, and anyone who has dealt with “reviewer 2” knows how much randomness is involved. The idea that this system consistently identifies excellence is difficult to defend.

More concerning is the effect it has on people. If you define success through a checklist of measurable achievements, then not meeting those benchmarks inevitably feels like falling behind. And that perception, of constantly not quite being enough, is what damages individuals and, over time, the system itself.

The other approach is at first glance less structured. It is not random, but it is guided by something harder to quantify. You follow questions that seem important, even if they are niche. You work on problems because they matter – first above all to patients and their caregivers, but also to clinical colleagues, and, importantly, to yourself. External validation becomes secondary. Not irrelevant, but not decisive either. The direction is set internally, not negotiated with the system.

Both approaches exist in the same institutions, often in the same people. But usually, one dominates.

I have been thinking about this again recently because I reapplied to a grant scheme I had applied to before. The first time, I did not get funded. At the time, that was frustrating in a very specific way. Not just because of the rejection itself, but because it felt as if the topic and its relevance had not been fully seen.

In rare disease research, this tension is almost built in. The patient groups are small by definition. If you look only at numbers, the impact appears limited. But these diseases are usually highly complex. If you manage to understand even a small part of the mechanism, or improve diagnosis or prognosis, or open a path toward new (or just any) treatment, the impact is disproportionate. It matters in a very direct way.

Recently, I went back and reread that old proposal. And what stood out was something I had not framed explicitly before: despite not receiving the funding, I had ended up doing essentially all of the work I had proposed.

Not in the same structured way, and not on the same timeline. But piece by piece, the questions had been addressed. The experiments had been done. The collaborations had formed. The data exists.

This was not about proving reviewers wrong. It was „simpler“. I continued because I was convinced the questions mattered. That conviction turned out to be more persistent than the disappointment.

Working this way is not efficient in the conventional sense. You spend time finding resources you do not have. You rely on people who engage without immediate return. You move across disciplines and learn as you go. Progress is uneven, and recognition often lags behind.

But something else happens. You connect with people who think in a similar way, often in unexpected places. The common factor is not institutional alignment, but shared commitment to a specific problem. To me these collaborations are more genuine.

There is no hierarchy between these approaches. They optimize for different things. Ideally, they would overlap. Often, they do not.

For me, revisiting that proposal clarified one thing. Even without funding, the work happened. Not because it was easy, but because it felt necessary. That is probably the only stable criterion in the long run. Not whether something is widely recognized, but whether it remains worth doing despite the friction.

There is a place for that kind of work. It may be small and not always visible. But it exists. And for the people it reaches, it matters.

Lack of recognition does not mean lack of relevance. And recognition does not guarantee it either.