> For the complete documentation index, see [llms.txt](https://sexytrees.savimbo.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://sexytrees.savimbo.com/practice-guide/chagras/reward-protocol.md).

# How are chagras rewarded?

<mark style="color:$danger;">This is a</mark> [<mark style="color:$danger;">bricolage</mark>](broken://pages/sU80QbSDJl3ALyzYPg18) <mark style="color:$danger;">protocol; which means we are building it in public! Some pages are under construction — but check back soon its updating fast!</mark>&#x20;

This protocol treats chagras as a *black box* system. In other words, we can see the inputs and the outputs, but we can't measure what is happening inside the system.&#x20;

There are lots of systems like this in the world. For instance, machine learning is a type of AI that uses inputs and outputs to train and operate. We don't necessarily have to understand things fully to reward or work with them. And sometimes taking things down into their component parts actually destroys the understanding (this is called reductionism).&#x20;

The reality is that yes, most Indigenous Peoples have a very good understanding of the internal operations of chagras, but this understanding takes a lifetime to learn and properly teach, which is why elders are usually the ones teaching.&#x20;

We also respect community and cultural privacy, and as a core policy do not store traditional ecological knowledge (TEK) when it's not required for trade protocols.&#x20;

Which is to say simply that chagras are rewarded by peer-validation on a time-bound protoco.&#x20;


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