What I'm suggesting with the above, is that there is nothing magical or distinctive about the mechanisms that generate consciousness vs. those that generate the understanding of semantics, grammar, syntax in a GPT or the ability to keep a pole in vertical position on a rolling cart with some reinforcement learning. Instead, it views consciousness as the mental model that is generated by a sufficiently complex intelligence (biological or not) when it has the ability to perceive inputs of its environment, and crucially, of itself. That is, a sufficiently complex brain with the ability to observe its environment and itself, will inevitably generate a model of both and their relationship. The model of itself and how it distinguishes itself from the environment is what I think is consciousness.
What I mean with emergent is that this mental model progressively becomes more and more rich ("emerges") as the cognitive abilities becomes more complex and the inputs of itself and the environment increase. A tapeworm with a very minimal central nervous system, scarce sensory inputs of the environment, and likely even less of itself will develop an excessively simple model that can hardly be recognized as consciousness. As you scale the cognitive abilities and the inputs it processes of both; environment and itself, a richer model of both will emerge. And that thing will start to look a whole lot like consciousness.