Your situation isn’t unusual for people with an interest in less-studied taxa and parts of the world sparsely populated with smartphone-equipped observers. But as others have said, the RG distinction isn’t really as critical as it might seem. If you’re comfortable with the IDs you’re able to provide, don’t worry too much that no-one is yet able to confirm them.
The main practical effect of reaching RG is that the observation details are synced to GBIF and will then show up as a data point in their matches and searches. But just because many of your tortoise beetle observations are still showing as “needs ID” doesn’t prevent them from being used in research. If we imagine an entomologist who wants to use iNat data for research on Ugandan tortoise beetles, they’re probably going to start looking at your observations and adding their own IDs which will mean many of them reach research grade. Even if they don’t add any IDs, datasets they download for analysis can still include “needs id” observations. It’s entirely up to the researcher whether they want to limit their scope to RG observations, and for sparsely IDed taxa like these, that constraint would be quite limiting. Better to take all data and use other quality control measures (including to validate RG observations).
Even so, it’s certainly more satisfying to have RG confirmation of your IDs, and there are several ways to achieve that:
Time is the most certain! iNat continues to grow exponentially, and the fastest growth is occurring in formerly poorly represented countries, so it’s not unreasonable to expect other people with an interest in East African entomology to join the platform, contribute their own observations and ID some of yours.
You can also try to encourage specialists in your field of interest (e.g. Prof. Borowiec) to join the platform and add IDs directly. This does happen fairly often and iNat can be a rewarding source of data even for very experienced academics. Sometimes academics can get frustrated with some of iNat’s principles. I’d say some of the bigger challenges are:
- that iNat treats all identifiers equally, with no automatic distinction between a tenured entomology professor and a high-school student (likely to be hugely mitigated by the fact that very few users are IDing African Coleoptera),
- that computer vision can lead to wildly incorrect IDs at times (ultimately mitigated by adding correct IDs with a brief rationale, and by accumulating enough correctly identified observations of a taxon for computer vision to learn the distinction) and
- that iNat’s taxonomy may currently appear “incorrect” in some respects, which can be resolved by flagging the taxon for attention by users with curator status (you might want to request this yourself if you’re at the point where you can judge the research and assess the consensus on which taxa are valid).
Researchers are also very busy already, but most are interested in helping advance knowledge of their specialist field and many do find identifying iNat observations informative.
Lastly, I’d really encourage you to use your growing knowledge to contribute IDs to other people’s observations. I doubt there are many users adding IDs for insects in East Africa, and refining IDs on those observations as far as you can be confident would be a great help. There’s a good chance that will also lead to developing the knowledge of other iNat users who will eventually have the skill to ID your own observations.