This research bridges the gap between claimed and actual ethical behavior by analyzing subtle "hidden honest signals" in language using AI and Natural Language Processing (NLP). It categorizes individuals into four "tribes": "doves" (ethical, collaborative), "wolves" (loyal, diligent), "sharks" (competitive, aggressive), and "parasites" (self-serving, exploitative). Using data from migrant workers in Taiwan, the study examines how ethical behavior correlates with productivity in healthcare and manufacturing sectors. Results show that ethical behavior influences work outcomes, though not always in expected ways. The findings suggest that developing ethical training programs could improve productivity, particularly for migrant workers in these settings.