The inference that supply-side feedback loops and preference mismatches demonstrate algorithms cause affective polarization fails because it conflates exposure changes with attitude changes that experiments do not detect.

[DEFENSE-UNDERCUT → v3z3sn] Milli et al. (2025) found that users did not prefer algorithmically selected political tweets, but this preference mismatch does not establish that amplified content causes affective polarization at the 10 percent threshold. Guess et al. (2023) found that switching to chronological feeds substantially changed content exposure but did not detectably change affective polarization, showing exposure changes do not automatically produce attitude changes. Reuning et al. (2022) documented asymmetric share patterns after the MSI change, but share counts are an engagement metric, not a measure of downstream affective polarization among content consumers. Therefore, The inference that supply-side feedback loops and preference mismatches demonstrate algorithms cause affective polarization fails because it conflates exposure changes with attitude changes that experiments do not detect. (Warrant: Documenting that algorithms change content supply and exposure patterns does not establish those changes cause affective polarization when direct experimental tests of the attitude link find nulls.)

• Milli et al. (2025) found that users did not prefer algorithmically selected political tweets, but this preference mismatch does not establish that amplified content causes affective polarization at the 10 percent threshold.
• Guess et al. (2023) found that switching to chronological feeds substantially changed content exposure but did not detectably change affective polarization, showing exposure changes do not automatically produce attitude changes.
• Reuning et al. (2022) documented asymmetric share patterns after the MSI change, but share counts are an engagement metric, not a measure of downstream affective polarization among content consumers.

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

• Is the literature really agreed that defects of kind K bias inferences in direction B, or is the bias direction itself contested?Open
• Does study S actually have defect D, or is the description of S inaccurate?Open
• Is the expected magnitude of the bias from D large enough to overturn S's reported effect, or is the effect robust to plausible bias corrections?Open
• Has S (or a follow-up study) performed a robustness check or sensitivity analysis that addresses defect D directly?Open
• Is this critique applied consistently — i.e., would it apply to studies on the other side of the debate that share the same defect kind K?Open
• Is H supported by independent studies that do not share defect D, such that S's defect does not undermine H itself?Open

No one has cited this argument yet.

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.