  In this paper, we address the concept of "alignment" in large language models
(LLMs) through the lens of post-structuralist socio-political theory,
specifically examining its parallels to empty signifiers. To establish a shared
vocabulary around how abstract concepts of alignment are operationalised in
empirical datasets, we propose a framework that demarcates: 1) which dimensions
of model behaviour are considered important, then 2) how meanings and
definitions are ascribed to these dimensions, and by whom. We situate existing
empirical literature and provide guidance on deciding which paradigm to follow.
Through this framework, we aim to foster a culture of transparency and critical
evaluation, aiding the community in navigating the complexities of aligning
LLMs with human populations.
