A development team is using a feedback-based learning process to train a large language model to be better at self-correction. Their method involves generating two responses to a user's prompt. Human labelers then select the 'better' response. The team's instructions to the labelers are simple: 'Always choose the factually correct response. If both are correct, choose the more helpful one. If both are incorrect, mark them as equally bad.'

Critically evaluate this training strategy. Is it the most effective way to specifically encourage and activate the model's ability to self-correct? Justify your evaluation and propose one specific improvement to the labeler instructions that would more directly train this capability.