Protocol for the classification of pre-migration decisions in the information and analytical support of migration policy

The object of the study is the informational and analytical support for the management cycle in the migration sector at the pre-migration stage. The subject of the study is a reproducible classification protocol of the minimum units of utterance ("atoms") based on the functional elements of pre-migration decisions. The author examines the problem of comparability of materials of different natures: digital texts and interviews. In the absence of a unified procedure, comparisons often reflect the genre and cohesion of the source rather than the structure of the decision. It is shown that standardizing the unit of analysis significantly reduces the influence of platform constraints and differences in the discursive practices of sources. Special attention is given to defining the atom, the limitations of acceptable context, and the prohibition of speculation during coding. The author discusses in detail the input requirements for data, the research framework, and the role of service categories as a tool for quality control of the corpus and the boundaries of the subject field. The work employs a content-analytical coding protocol with procedural atomization, functional typology of categories, and a fixed contract for input data. Reliability is ensured through independent double coding of the subsample and assessment of consistency using Krippendorff’s alpha (α). The novelty of the research lies in the formalization of a classification methodological module that is separate from the stages of material collection and subsequent analytical synthesis. Five functional types of atoms are proposed (trigger, significant result, barrier, alternative, way to overcome the barrier), two service categories and a procedure for resolving borderline cases, including clarifying atomization A_ID.x. The main conclusions are as follows. Comparability is enhanced by standardizing the unit of analysis and referral rules rather than by expanding the context. Service categories allow for the recording of observation limitations and diagnosis of the quality of the input corpus. A pilot test on a corpus of digital texts showed high coding consistency (α=0.854; N=74). The results are applicable as input for monitoring and evaluating migration policy measures; the next step involves extended testing on a mixed corpus of "content + interviews."