Is pay gap reporting about transparency or accountability? This was the main theme of the House of Lords debate on Ethnicity Pay Gap Reporting (EPGR) on 25th October 2021, unlike the Commons debate that preceded it in September. The 9 peers who spoke could be split between those who see EPGR as an exercise in employer transparency and those who see EPGR as an exercise in employer accountability and I consider this to be a fundamental question that has not yet been answered. In this article, I will discuss the implications of both answers to this question for any future EPGR legislation.
The UK Parliament debated Ethnicity Pay Gap Reporting (EPGR) on 20th September 2021 in Westminster Hall. Seven MPs spoke in the hour long debate and, as debates go, I thought it was actually quite good. There was cross party consensus on the merits of EPGR but I saw a divide between those who recognise EPGR is complex and requires trade offs and those who think the complexities of EPGR can be solved with government guidance.
The UK Parliament is about to debate whether or not ethnicity pay gap reporting (EPGR) by UK employers should be made mandatory. The debate will start at 4.30pm on Monday 20th September 2021 and is a result of an e-petition reaching the threshold to require a parliamentary debate. To assist MPs, journalists, campaigners and anyone else interested in this debate, I have written a briefing note which lists 9 key points that need to be addressed during the debate.
On 30th September 2020, CL:AIRE (the industry body for the land contamination & remediation sector) published new professional guidance for “Comparing Soil Contamination Data with a Critical Concentration“. The 46-page document advises how to use statistics when assessing land contamination and deciding whether it is safe for development. I was the lead author of the guidance and I spent 4 years working with CL:AIRE’s steering committee on what the guidance should cover. The 4 years were bookended by statement & editorial published by the ASA (American Statistical Association) on the use & misuse of P-Values in 2016 & 2019 respectively and in writing this guidance I felt was I an ambassador for turning those into something that could used by non-statisticians to make real life decisions that have an impact on us all.
Updated on 14th May 2020. New and modified links are italicised.
The Coronavirus Pandemic is a worldwide challenge many of us will have not experienced before. It is natural to want to seek information on the risks and in our world today, it has never been easier to find data, analyses and opinions. Unfortunately, a lot of what you will read out there is either unhelpful or actively misleading. As an independent statistician with 30 years experience of explaining statistics to non-statisticians, my contribution to this crisis will be to try and sort the good from the bad hence this post. [Read more…] about Coronavirus #1 – Useful Data and Links
The city of Bath is among a number of cities in the UK tasked with reducing Nitrogen Oxide (NOx) emissions. NOx pollution is thought to contribute to poor health and the government has required clean air plans from the relevant local authorities to be in place before 2021. I had no idea that this would result in my statistical expertise being needed to answer a political row over the BathBreathes2021 plans to charge cars driving into Bath and you can read my report to see what my answer was!
On June 5th 2019, I had the privilege of being able to talk to the Treasury Select Committee about the “Effectiveness of Gender Pay Gap Reporting“. My name was put forward by the Royal Statistical Society and we spent an hour discussing a number of issues with a particular focus on the Finance sector.
Mention P-values and most people will probably shudder at some memory of an incomprehensible lecture or lesson on statistical tests. Words like null hypotheses, t-tests, statistical significance might pop into your mind with little understanding of what they are about. What you may know is that scientists have to report a p-value for any experiment they do or do they?
The area of Statistical Inference is a core area of study for any statistician. Put simply, Inference means to infer from the observations you’ve made about your data and to draw conclusions about what might be happening in real life. There are two parts to Inference.
April 2018 was the deadline for submitting gender pay gap results and we now have the first detailed picture of how pay differs between men and women in the UK. A nifty government website can be used to look up pay gap details for any company employing more than 250 employees and you can also download the results for further analysis. So what will happen next? Will the data be used properly to inform debate about how men and women are paid or will it be misused for personal and political gain?
I believe this data can be of benefit to the debate around gender equality but my fear is that to begin with, it will be misused, misinterpreted and reinforce the saying “lies, damned lies and statistics”. So if you want to misuse gender pay gap data, who better to ask that a professional statistician like me who will show you how you can do this by commenting on 7 plausible statements.
Fake news has entered the political dictionary over the last year. Suddenly, politicians and commentators are worried that elections are being influenced by false stories being circulated that appear to be genuine. Social media platforms are under pressure to filter out such stories raising the old questions of censorship and “who guards the guards?” However, evidence on the extent and influence of fake news is thin on the ground.