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<title>Mind Your Own Data</title>
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  <title>Transparency is infrastructure</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/foi-disclosure-logs/</link>
  <description><![CDATA[ I’ve spent the last couple of months turning scattered, inconsistent FOI disclosure logs into a single searchable archive. This post examines the gap between mandated publication and meaningful transparency, and who ends up doing the work to close it. ]]></description>
  <guid>https://mindyourowndata.org/posts/foi-disclosure-logs/</guid>
  <pubDate>Mon, 27 Apr 2026 00:00:00 GMT</pubDate>
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  <title>Footy fields and tech giants: how the case for the social media ban was built</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/social-media-ban-language/</link>
  <description><![CDATA[ Australia’s teen social media ban came into effect on 10 December 2025, putting the country at the forefront of a global debate about children’s safety online. Three months on, it’s far too soon to know if the ban is working. But we can examine how the case for it was made: how the foundations were laid for such an ambitious policy, and what the rhetorical arc tells us about how political consent was built. ]]></description>
  <guid>https://mindyourowndata.org/posts/social-media-ban-language/</guid>
  <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
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  <title>Nobody’s responsible: inside the data broker supply chain</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/data-broker-supply-chains/</link>
  <description><![CDATA[ Data brokers hold detailed information about most Australians without their knowledge. When I spent several months making access requests to trace my own data through the supply chain, I found something more interesting than the data itself: nobody was responsible for it. ]]></description>
  <guid>https://mindyourowndata.org/posts/data-broker-supply-chains/</guid>
  <pubDate>Sun, 22 Feb 2026 00:00:00 GMT</pubDate>
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<item>
  <title>Feedback loops and the limits of responsibility</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/ml-feedback-loops/</link>
  <description><![CDATA[ Feedback loops in machine learning are often presented as a problem that arises in particular domains, with familiar examples in recommendation systems and predictive policing. These examples are usually treated as special cases. In this piece, I argue the opposite: feedback loops are the default condition of deployed machine learning systems, not a pathological edge case. Feedback loops are structurally inevitable once models are deployed into the world because of how we frame, evaluate, and govern these systems. ]]></description>
  <guid>https://mindyourowndata.org/posts/ml-feedback-loops/</guid>
  <pubDate>Mon, 26 Jan 2026 00:00:00 GMT</pubDate>
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<item>
  <title>Access rights in practice: reflections from 60 data access requests</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/app12-request-patterns/</link>
  <description><![CDATA[ In Australia, you have the right to access the personal information an organisation holds about you under Australian Privacy Principle 12 (APP 12). Over the past year, I’ve made 60 data access requests to a range of organisations, including charities, major retailers, and data brokers. The process revealed as much about organisational governance and privacy maturity as it did about the data itself. ]]></description>
  <guid>https://mindyourowndata.org/posts/app12-request-patterns/</guid>
  <pubDate>Sun, 18 Jan 2026 00:00:00 GMT</pubDate>
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  <title>Can disabled people…? What autocomplete reveals about views on disability</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/autosuggest-disability/</link>
  <description><![CDATA[ Inspired by Safiya Umoja Noble’s Algorithms of Oppression, this post explores a neglected area of autocomplete research. While stereotyping in search suggestions has been studied for race, gender, and other attributes, disability is largely absent from the literature. I report the results of a small audit of disability-related autocomplete queries across major search platforms. ]]></description>
  <guid>https://mindyourowndata.org/posts/autosuggest-disability/</guid>
  <pubDate>Sat, 17 Jan 2026 00:00:00 GMT</pubDate>
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  <title>A taxonomy of awkward conversations with stakeholders</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/difficult-conversations/</link>
  <description><![CDATA[ This post is about different categories of difficult conversations with stakeholders that you will almost inevitably encounter as a data scientist. I think of it as more of a taxonomy (and perhaps commiseration) than advice. Data scientists sit in an awkward place inside organisations. We’re expected to deliver authority, certainty, and progress, while working with uncertainty, partial information, and value judgements that rarely belong to data science alone. Many of the most uncomfortable conversations arise from that tension. ]]></description>
  <guid>https://mindyourowndata.org/posts/difficult-conversations/</guid>
  <pubDate>Thu, 08 Jan 2026 00:00:00 GMT</pubDate>
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<item>
  <title>Data ethics is your job</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/data-ethics-is-your-job/</link>
  <description><![CDATA[ All too often in data science projects, data ethics is treated as someone else’s responsibility. It sits with legal, governance, product, or a committee that meets occasionally and far away from the day-to-day work. If it comes up at all, it’s often well after the key decisions have been made about what gets built. This post argues that data ethics is not an optional extra. Data scientists are often uniquely positioned to identify ethical risks and potential harms, and that position comes with an obligation to take them seriously. ]]></description>
  <guid>https://mindyourowndata.org/posts/data-ethics-is-your-job/</guid>
  <pubDate>Wed, 07 Jan 2026 00:00:00 GMT</pubDate>
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<item>
  <title>Measuring how long things take is harder than it seems</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/right-censoring/</link>
  <description><![CDATA[ Measuring how long a process takes seems easy: start, stop, average. So it should disturb you to find out there’s an entire subfield of statistics devoted to it. This post looks at why time-to-event data is trickier than it seems and the mistakes people commonly make. ]]></description>
  <guid>https://mindyourowndata.org/posts/right-censoring/</guid>
  <pubDate>Sun, 14 Dec 2025 00:00:00 GMT</pubDate>
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  <title>The case against propensity modelling</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/case-against-propensity-modelling/</link>
  <description><![CDATA[ Propensity models look for patterns in past data to estimate how likely someone is to do something (buy, cancel, or upgrade). It’s a deceptively simple idea: train a model on who acted before and use it to predict who will act next. It sounds powerful, and in theory it should let you focus your efforts where they’ll have the most impact. In practice, the question propensity modelling answers is often the wrong one. ]]></description>
  <guid>https://mindyourowndata.org/posts/case-against-propensity-modelling/</guid>
  <pubDate>Mon, 03 Nov 2025 00:00:00 GMT</pubDate>
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  <title>Everything breaks eventually: data science lessons I’ve learned the hard way</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/lessons-learned-the-hard-way/</link>
  <description><![CDATA[ A few years in data science will give you strong opinions about strange things: Microsoft Excel, daylight saving time, unit tests. The beauty of this job is that things can always go wrong in new and interesting ways, but I’ve gradually accumulated some hard-won instincts about what’s most likely to break first. These are a few of the lessons I’ve learned the hard way on the technical side of the job. The human side deserves its own list (or possibly a thesis). ]]></description>
  <guid>https://mindyourowndata.org/posts/lessons-learned-the-hard-way/</guid>
  <pubDate>Wed, 08 Oct 2025 00:00:00 GMT</pubDate>
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  <title>The hidden work of data science projects</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/hidden-work/</link>
  <description><![CDATA[ You’ve probably heard the phrase “80% of data science is data cleaning.” It’s not totally wrong, but it is incomplete. While I agree that data science often involves surprisingly little modelling, the 80% line doesn’t do justice to the full range of non-modelling work that makes data projects succeed. These are the things that tend to go unnoticed and unappreciated if everything goes well — but skip them at your peril. ]]></description>
  <guid>https://mindyourowndata.org/posts/hidden-work/</guid>
  <pubDate>Thu, 02 Oct 2025 00:00:00 GMT</pubDate>
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  <title>ScoMo’s last hurrah?</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/scomo-last-hurrah/</link>
  <description><![CDATA[ When I started collecting and analysing Australian Prime Minister Scott Morrison’s speeches and interview transcripts over a year ago for a blog post, I hardly believed he would still be Prime Minister come the next election. With the election today, this is very possibly Scott Morrison’s last day as PM. In honour of the occasion, this is a special edition post about ScoMo’s language use during the election campaign. ]]></description>
  <guid>https://mindyourowndata.org/posts/scomo-last-hurrah/</guid>
  <pubDate>Sat, 21 May 2022 00:00:00 GMT</pubDate>
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  <title>Automated web scraping using GitLab CI/CD</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/automated-scripts-gitlab/</link>
  <description><![CDATA[ When working on data projects that rely on regularly updated sources, it’s easy to end up with a manual refresh process — running a series of scripts locally, saving the results, and uploading the new data wherever it’s needed. That approach works fine at first, but quickly becomes repetitive and error-prone as the project grows. This post describes how I used GitLab CI/CD and AWS S3 to automate a set of R scripts that collect, clean, and process data on a schedule. ]]></description>
  <guid>https://mindyourowndata.org/posts/automated-scripts-gitlab/</guid>
  <pubDate>Mon, 19 Jul 2021 00:00:00 GMT</pubDate>
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<item>
  <title>The Prime Minister’s speech: A textual analysis</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/scomo-speech/</link>
  <description><![CDATA[ Since becoming Prime Minister in 2018, Scott Morrison has spoken publicly almost every day. Transcripts of all speeches, interviews, and press conferences are available on the Prime Minister’s website, which means we can analyse ScoMo’s language over this whole period (August 2018 - March 2021). ]]></description>
  <guid>https://mindyourowndata.org/posts/scomo-speech/</guid>
  <pubDate>Sun, 04 Apr 2021 00:00:00 GMT</pubDate>
</item>
<item>
  <title>UI/UX and data science</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/ui-ux-and-data-science/</link>
  <description><![CDATA[ In this post I’ll talk about what I learned from two courses I recently took on Coursera: Visual Elements of User Interface Design and UX Design Fundamentals (both taught by Michael Worthington from the California Institute of the Arts). ]]></description>
  <guid>https://mindyourowndata.org/posts/ui-ux-and-data-science/</guid>
  <pubDate>Mon, 26 Oct 2020 00:00:00 GMT</pubDate>
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  <title>Unsupervised learning and lessons from the science of personality testing</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/personality-tests/</link>
  <description><![CDATA[ After completing a personality test as part of a job application, I recently became interested in the science and statistics of personality testing. This is part of the field of psychometrics, which is concerned with the measurement of mental traits and aptitudes. Psychometrics is a fascinating field in itself, but the more I read the more I started to see parallels between the challenges of personality testing and those of unsupervised learning. In this post I’ll discuss some of the things that make personality testing difficult and how the the field of personality testing deals with these challenges. While personality testing does have some unique challenges, often there are lessons to be learned from the field that can be applied to unsupervised learning problems more generally. ]]></description>
  <guid>https://mindyourowndata.org/posts/personality-tests/</guid>
  <pubDate>Mon, 25 May 2020 00:00:00 GMT</pubDate>
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<item>
  <title>A deep dive into short circuit evaluation</title>
  <dc:creator>Gabrielle Josling</dc:creator>
  <link>https://mindyourowndata.org/posts/short-circuiting/</link>
  <description><![CDATA[ One consequence of not having ever learned programming in any systematic way is that sometimes I come across a very unexpected behaviour that I don’t really have the language to describe (or more problematically, to Google). Recently when this happened I was led down a very interesting rabbit hole to the idea of short circuit evaluation. Importantly, I learned that my mental model for how logical operators work was not quite right. ]]></description>
  <guid>https://mindyourowndata.org/posts/short-circuiting/</guid>
  <pubDate>Fri, 28 Feb 2020 00:00:00 GMT</pubDate>
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