A Gordon: Researcher — Prolific Citations Library

Explore 3 peer-reviewed studies by A Gordon in Human-centered AI evaluation and Bayesian statistics (2022–2026). Discover research powered by Prolific's participant panel.

This page lists 3 peer-reviewed papers authored or co-authored by A Gordon in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (3 of 3)

Unpacking Human Preference for LLMs: Demographically Aware Evaluation with the HUMAINE Framework

Authors: N Petrova, A Gordon, E Blindow

Year: 2026

Published in: Open review

Institution: Prolific

Research Area: Human-centered AI evaluation, Bayesian statistics, Responsible AI, AI alignment, LLM Evaluation

Discipline: Machine Learning, Artificial Intelligence

The study introduces HUMAINE, a multidimensional evaluation framework for LLMs, revealing demographic-specific preference variations and ranking google/gemini-2.5-pro as the top-performing model with a posterior probability of 95.6%.

Methods: Multi-turn naturalistic conversations analyzed using a hierarchical Bayesian Bradley-Terry-Davidson model with post-stratification to census data, stratified across 22 demographic groups.

Key Findings: Performance of 28 LLMs across five human-centric dimensions, accounting for demographic-specific preferences.

Sample Size: 23404
What over 1,000,000 participants tell us about online research protocols

Authors: J Tomczak, A Gordon, J Adams, JS Pickering

Year: 2023

Published in: Frontiers in Human ..., 2023 - frontiersin.org

Institution: Prolific, University of Leeds, Gorilla

Research Area: Online Research Protocols, Human Neuroscience, Behavioral Research

Discipline: Human Neuroscience

Citations: 31
Data quality of platforms and panels for online behavioral research

Authors: E Peer, D Rothschild, A Gordon, E Damer

Year: 2022

Published in: Behavior Research Methods, 2022 - Springer

Institution: The Hebrew University of Jerusalem, Microsoft Research, Prolific

Research Area: Online Behavioral Research, Data Quality, Research Methods

Discipline: Computational Social Science, Behavioral Research

Citations: 2112