alienation-analysis

Alienation analysis assesses severity by computing structured scores from your survey indicators across labor, social, consumption, and technology domains, outputting severity levels from micro to severe. You provide the metric keys, and the engine returns dimension scores and a primary alienation type.

Marxist critique diagnosis works by turning qualitative alienation concepts into quantitative scores across labor, social, consumption, and technology dimensions. It computes specific sub-scores like work autonomy and relationship quality to produce an interpretable severity level for academic assessment.

Yes, batch processing supports group alienation risk assessment by returning per-individual diagnostic results alongside summary statistics. It calculates means, medians, and distributions of alienation types and severity levels across the entire batch.

Intervention priorities are generated by identifying risk factors that cross critical cutoffs in your alienation scores. The engine ranks these interventions based on the primary alienation type diagnosed, directly supporting research-to-intervention workflows.

Inputs must match the required metric keys for labor, social, consumption, and technology domains, such as work autonomy, consumption rationality, and technology dependency. Providing properly structured survey indicators allows the engine to compute the dimension scores and severity levels.

The best way to diagnose technology dependency is by using the technology domain scoring, which evaluates digital wellbeing, balance, and dependency indicators. This produces a specific dimension score and identifies risk factors if critical cutoffs are crossed.