Aligning Intraobserver Agreement by Transitivity

09/29/2020
by   Jacopo Amidei, et al.
0

Annotation reproducibility and accuracy rely on good consistency within annotators. We propose a novel method for measuring within annotator consistency or annotator Intraobserver Agreement (IA). The proposed approach is based on transitivity, a measure that has been thoroughly studied in the context of rational decision-making. The transitivity measure, in contrast with the commonly used test-retest strategy for annotator IA, is less sensitive to the several types of bias introduced by the test-retest strategy. We present a representation theorem to the effect that relative judgement data that meet transitivity can be mapped to a scale (in terms of measurement theory). We also discuss a further application of transitivity as part of data collection design for addressing the problem of the quadratic complexity of data collection of relative judgements.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/06/2020

Easy, Reproducible and Quality-Controlled Data Collection with Crowdaq

High-quality and large-scale data are key to success for AI systems. How...
research
09/10/2018

sklarsomega: An R Package for Measuring Agreement Using Sklar's Omega Coefficient

R package sklarsomega provides tools for measuring agreement using Sklar...
research
01/25/2023

Consistency is Key: Disentangling Label Variation in Natural Language Processing with Intra-Annotator Agreement

We commonly use agreement measures to assess the utility of judgements m...
research
11/05/2020

Measuring Data Collection Quality for Community Healthcare

Machine learning has tremendous potential to provide targeted interventi...
research
06/26/2023

Inter-Annotator Agreement in the Wild: Uncovering Its Emerging Roles and Considerations in Real-World Scenarios

Inter-Annotator Agreement (IAA) is commonly used as a measure of label c...
research
04/14/2023

Measuring Stakeholder Agreement and Stability in a Decentralised Organisation

A decentralised organisation (DO) is a multi-stakeholder institution whe...
research
06/21/2021

Data Optimisation for a Deep Learning Recommender System

This paper advocates privacy preserving requirements on collection of us...

Please sign up or login with your details

Forgot password? Click here to reset