Individual-level causal effects of algorithmic animosity amplification on affective polarization, operating through a mechanism present on multiple platforms reaching a supermajority of US adults, make it plausible — though not formally demonstrated — that the population-level contribution exceeds 10% of observed affective polarization growth.

[NARROW-VARIANT] Piccardi et al. (2025) found a >2-point feeling-thermometer shift from 10 days of algorithmic reranking on a single platform. As of 2024, approximately 70 percent of US adults use at least one in-scope platform for 30+ minutes per week, exposing a supermajority of the adult population to engagement-optimized algorithmic feeds. The out-group animosity channel identified by Rathje et al. (2021) — posts about political opponents receiving double the engagement — operates on both Facebook and Twitter, the two largest political-content platforms in the US. Therefore (narrowed), Individual-level causal effects of algorithmic animosity amplification on affective polarization, operating through a mechanism present on multiple platforms reaching a supermajority of US adults, make it plausible — though not formally demonstrated — that the population-level contribution exceeds 10% of observed affective polarization growth.

• Piccardi et al. (2025) found a >2-point feeling-thermometer shift from 10 days of algorithmic reranking on a single platform.
• As of 2024, approximately 70 percent of US adults use at least one in-scope platform for 30+ minutes per week, exposing a supermajority of the adult population to engagement-optimized algorithmic feeds.
• The out-group animosity channel identified by Rathje et al. (2021) — posts about political opponents receiving double the engagement — operates on both Facebook and Twitter, the two largest political-content platforms in the US.

These are challenges this argument’s reasoning pattern must still withstand. Answering them on Isonomia strengthens the argument.

• Does the operational measure of F in the sample actually capture F as it is meant in the population-level claim?Open
• Is the sample actually representative of the target population on the dimensions that matter for F (demographics, behavior, time period, platform mix)?Open
• Is the sample large enough to support the precision (margin m) being claimed?Open
• Does the conclusion stay within the population P from which S was drawn, or does it overreach (different country, different time period, different platform)?Open
• Was the sample drawn or recruited in a way that systematically biases the proportion of F (e.g., volunteer bias, opt-in panels, attrition)?Open

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No arguments cite this one yet — no one has built on or contested it. That is an absence of engagement, not a finding of soundness. Build on or contest it on Isonomia to change that.