The Pearson correlation matrix between Pn, MDA as well as yield and yield related parameters under LTS at tillering (T), booting (B), and heading (H) stages. حسب Lifeng Guo (17320116)

Effects of LTS on G_s. حسب Lifeng Guo (17320116)

Effects of LTS on T_r. حسب Lifeng Guo (17320116)

Effects of LTS on pollen viability. حسب Lifeng Guo (17320116)

Effects of LTS on MDA. حسب Lifeng Guo (17320116)

Effects of LTS on proline. حسب Lifeng Guo (17320116)

Effects of LTS on EL. حسب Lifeng Guo (17320116)

Effects of LTS on SOD. حسب Lifeng Guo (17320116)

Effects of LTS on CAT. حسب Lifeng Guo (17320116)

Effects of LTS on the soluble protein. حسب Lifeng Guo (17320116)

Effects of LTS on POD. حسب Lifeng Guo (17320116)

Effects of LTS on P_n. حسب Lifeng Guo (17320116)

Effects of LTS on the soluble sugar. حسب Lifeng Guo (17320116)

Effects of LTS on C_i. حسب Lifeng Guo (17320116)

Effects of LTS on H₂O₂. حسب Lifeng Guo (17320116)

Effects of LTS on the production rate of O₂^-. حسب Lifeng Guo (17320116)

Preference for the EIA – conjoint results. حسب Mehdi Mourali (10170245)

"…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …"

Marginal means – Pooled across scenarios. حسب Mehdi Mourali (10170245)

"…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …"

Sample attribute table. حسب Mehdi Mourali (10170245)

"…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …"

Subgroup analysis – Political affiliation. حسب Mehdi Mourali (10170245)

"…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …"