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It leverages a setting where teachers assigned both grades and rankings within each grade, enabling a local randomization design that compares student types adjacent to grade boundaries. The approach estimates imbalance in student characteristics and identifies systematic bias favoring female and white students. The grading bias has real downstream effects: students near thresholds are more likely to attend university. The method is broadly applicable to systems with multiple thresholds and subjective rankings.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/measuring-systematic-gaps-in-teacher-judgement-a-new-approach/583335/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/measuring-systematic-gaps-in-teacher-judgement-a-new-approach/583335.png","ImageObject",300,407,{"name":92,"@type":93},"Jake","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-20","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":19},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main goal of the paper?","Question",{"text":112,"@type":113},"To measure systematic biases in subjective evaluations using a new testing approach built on grade boundaries and within-grade rankings.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the method estimate bias around grade thresholds?",{"text":117,"@type":113},"It compares student types immediately above and below each grade boundary and treats discontinuous changes in their representation as evidence of teacher bias.",{"name":119,"@type":110,"acceptedAnswer":120},"What did the authors find about teacher grading decisions?",{"text":121,"@type":113},"The analysis reveals systematic bias favoring female and white students, and students just above thresholds show higher university attendance rates.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},583335,1792172025,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":19,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},962084928904,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Discussion Paper  \nISSN 2042-2695  \nNo. 2178  \nMay 2026  \nMeasuring systematic gaps in  \nteacher judgement: a new approach  \nOliver Cassagneau-Francis Richard Murphy Lindsey Macmillan  \nGill Wyness  \nAbstract  \nWe propose a new approach to test for systematic biases in subjective evaluations. We exploit a setting where teachers were required to assign students both grades and rankings within each grade. Comparing students immediately adjacent to grade boundaries, we apply a local randomization approach to estimate imbalance in student characteristics. Our findings reveal systematic bias favoring female and white students. These grading decisions carry real consequences: students just above the grade threshold are significantly more likely to attend university. Our approach can be applied whenever there is a system with many thresholds and subjective rankings.  \nKeywords: teacher bias; gender; stereotypes; proportions; test optional  \nJEL codes: C10; C25; I23; I24; J15  \nThis paper was produced as part of the Education Programme. The Centre for Economic Performance is financed by the Economic and Social Research Council.  \nWe thank Ofqual, DfE and UCAS for making this valuable dataset available to researchers. This work was generously supported by an ADR UK Research Fellowship. The usual disclaimers apply.  \nOliver Cassagneau-Francis, Centre for Education Policy and Equalising Opportunities (CEPEO), UCL. Richard Murphy, UT Austin, NBER, IZA, CESifo. Lindsey Macmillan, Centre for Education Policy and Equalising Opportunities (CEPEO), UCL. Gill Wyness, CEPEO and Centre for Economic Performance at the London School of Economics.  \nPublished by  \nCentre for Economic Performance  \nLondon School of Economic and Political Science Houghton Street  \nLondon WC2A 2AE  \nAll rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means without the prior permission in writing of the publisher nor be issued to the public or circulated in any form other than that in which it is published.  \nRequests for permission to reproduce any article or part of the Working Paper should be sent to the editor atthe above address.  \n􀂔 O. Cassagneau-Francis, R. Murphy, L. Macmillan and G. Wyness, submitted 2026.  \n1 Introduction  \nSubjective evaluations play a pivotal role in many high-stakes decisions, including hiring and promotion in the labor market (Taylor and Yildirim, 2011 ; Li and Kahn, 2018), bailand sentencing in the justice system (Ichino et al. , 2003 ; Arnold et al. , 2018 ; Cohen and Yang, 2019 ; Chyn et al. , 2025), and assessments of pupil performance in education (Lavy, 2008 ; ?) . The prevailing concern with subjective assessment is its potential for bias. Yet there are inherent difficulties in measuring this bias, precisely due to the subjective nature of these evaluations.1  \nDespite these concerns, many countries (including Australia, Portugal, the UK, and the USA) are increasingly relying on subjective evaluation metrics.2 This shift often involves moving away from standardized test scores in favour of teacher assessments, such as GPA, particularly in the university application process (Dessein et al. , 2025) . This removal of standardized test scores has been typically motivated by a desire for equity. However, the presence of bias in the subjective assessments that replace standardized tests is a clear threat to this goal.  \nBut measuring bias in subjective assessment is inherently challenging. Existing studies measuring teacher bias either require primary data collection, limiting the sample size and representativeness (Hinnerich et al. , 2011 ; Hanna and Linden, 2012 ; Alesina et al. , 2018 ; Carlana, 2019), or rely on assumptions to compare achievements on blind and nonblind assessments (Lavy, 2008 ; Lavy and Sand, 2015 ; Terrier, 2020 ; Burgess et al. , 2022 ; Graetz and Karimi, 2022 ; Lavy and Megalokonomou, 2024) . In this paper, we develop a novel approach","cbCaijG8QdaWF2Zx","https://ap.wps.com/l/cbCaijG8QdaWF2Zx","pdf",8793739,44,"English","# Abstract\n# Introduction\n## The role and challenges of subjective evaluation\n## Existing approaches to measuring teacher bias\n## The paper’s proposed method\n## Application to A-level teacher assessments","[{\"question\":\"What is the main goal of the paper?\",\"answer\":\"To measure systematic biases in subjective evaluations using a new testing approach built on grade boundaries and within-grade rankings.\"},{\"question\":\"How does the method estimate bias around grade thresholds?\",\"answer\":\"It compares student types immediately above and below each grade boundary and treats discontinuous changes in their representation as evidence of teacher bias.\"},{\"question\":\"What did the authors find about teacher grading decisions?\",\"answer\":\"The analysis reveals systematic bias favoring female and white students, and students just above thresholds show higher university attendance rates.\"}]","Measuring systematic gaps in teacher judgement - a new approach | PDF",1792046825,111]