Through a combination of trial-and-error, latent knowledge built up from using WordPress for over 15 years, and ChatGPT, I’ve found a way of generating more visitor-friendly archive pages for each of my blog post categories.
The reason I’m thinking about this at the moment is because I’m publishing a lot relating to my MSc in Systems Thinking in Practice, and am linking to the category archive at the top of each post.
I’ll not go into too much detail, but I wanted to replicate the style of my main archives page which is generated using the Simple Yearly Archive plugin. I duplicated archive.php in my themes folder, renamed it category.php and then tinkered around with it. ChatGPT was excellent at giving me the code I needed to do the things I wanted, including for the category RSS feed.
I then looked my Open Badges category archives page to ensure everything was working, and noticed that at some time in the past I’d added some code to change the background colour. After taking a while to figure out how I’d done that, I discovered that it’s super-easy to do by going to ‘Appearance’ then ‘Customise’ in the admin dashboard, then adding ‘Additional CSS’.
Here’s what I used to change the background colour of the MSc Systems Thinking category:
To improve this further, I’d organise the category page by tag as well as date. But that’s quite enough for this morning. I’ve got some proper work to do!
Apparently, the difference between ‘inquiry’ and ‘enquiry’ isn’t simply an example of variation between American and British English. Rather, as the course materials note, “recent British usage enquire has tended to mean ‘to ask’ and inquire has meant ‘to investigate’, but this difference is not apparent everywhere”. The TB872 module therefore uses ‘inquiry’ in the sense of an exploration or investigation.
We understand ‘systemic inquiry’ as a meta-process for project or programme managing suited to some, but not all, situations. A systemic inquiry can precede or run in parallel with a programme or project. Inquiry is a form of practice as well as a disposition and it is enhanced by acknowledging uncertainty from the start i.e. an attitude of avoiding the hubris of certainty.
To be honest, I didn’t really understand Activity 1.18, so I asked my “little robot friend” (I’ve created a GPT using the TB872 course materials, being sure to tick the option not to use them for ChatGPT’s training data). It said that this activity is an exercise in self-examination and a way to align my personal or professional practices with the principles of managing systemic change. This activity, and therefore this blog post, is only about setting it up.
As such, I need to consider:
Reflecting on my current practice: particularly in terms of managing changes in complex systems. This might involve considering how I approach problems, make decisions, and interact with others in situations that require systemic thinking.
Identifying Practices: I need to think about specific practices or habits I currently use when faced with systemic challenges. This could include both formal methods and informal strategies that I employ in professional or personal contexts.
Analysing the effectiveness of these practices: for example, are there areas where my approach works well? Are there aspects that could be improved? Through this analysis, I should be able to recognise strengths as well as areas for development in my systemic practice.
Praxis: by connecting my personal practices with theoretical concepts and frameworks I’m learning module, I should figure out how my methods align with or diverge from the principles of systems thinking.
Iteration: my systems literacy will improve over time, so I only need to consider what I would call System Inquiry v0.1. As I progress through the module I’ll then integrate new insights and learning.
There are so many areas I could cover, but given that I’m blogging publicly about all of this I think I’ll probably steer clear of anything solely related to my family. Instead I’ll focus more on personal or work-related things.
For example (again, with the help of my little robot friend), I could consider:
Decision-making processes: how do I make decisions, especially in complex situations? Do I consider multiple perspectives? How do I deal with uncertainty or conflicting information?
Problem-solving approaches: how do I approach problem-solving? Do I tend to look at problems in isolation, or do I consider the wider system and potential ripple effects of my solutions?
Communication & collaboration: if I consider my communication and collaboration practices, particularly in group settings or teams, how do I ensure diverse viewpoints are considered? How do I manage conflicts or integrate different ideas?
Change management: by reflecting on a specific instance where I was involved in managing change, what were the strategies I used, the challenges I faced, and the outcomes that were achieved?
Workplace practices: what are the systems and processes within my organisation. How do they impact my work? Are there inefficiencies or areas for improvement that a systems thinking approach could address?
Personal habits & routines: looking at my daily habits and routines, how do these contribute to my overall well-being or goals? Are there systemic factors influencing these habits?
Handling stress & complexity: reflecting on how I handle stress and complex situations, do I have strategies for maintaining a holistic perspective and not getting overwhelmed by details?
Balancing different life roles: considering how I balance different roles in my life (e.g., professional, parent, community member), how do these roles interact and influence each other?
Learning & education: thinking about my approach to learning and education, how do I integrate new knowledge into my practice? Do I consider the broader implications of what I learn?
Community engagement: in terms of community activities in which I’ve involved, I could consider how I contribute and what systemic factors affect the community. How do I approach community issues from a systems perspective?
It was useful to ask for some options, as otherwise I’d probably just have looked about something specific to our co-op. Instead, I think I’ll reflect on my practice in terms of how I remain productive despite all of the different things that could hinder that (health, time pressures due to family commitments, study, etc.)
I’ll refine this further as I get into things a bit more, but thinking about my ‘practice’ in terms of the way I set up my life to be as (sustainably) productive as possible seems like a good start.
Just over nine years ago, Team Belshaw needed to find somewhere to live. I’d been told by my employer at the time that, for various reasons, our dream of moving to Gozo couldn’t go ahead. But we still wanted to sell our house. So we moved from a four-bedroom detached house into a two-bedroom terrace in Morpeth.
It all worked out well. We ended up buying the house and converting the loft. I had a home office as the garage, separate to the house, was already converted for that purpose. Our neighbours have proved been amazing. Being so close to the centre of town and their schools it’s been a lovely place to raise our kids.
However, it’s never been our long-term plan to stay put; we’ve always been looking for somewhere else. The pandemic and then our son’s GCSE exams put off the sale of our house, but this year we finally put it on the market. Two weeks later we accepted an offer. On the same day, we had an offer accepted on a house which backs onto a river.
Not this house! Just an illustrative photo of the 2008 floods.
Now, anyone who knows Morpeth knows that it flooded quite spectacularly in 2008 and then again in 2012. The Environment Agency has spent a lot of money on various flood defences including an underground reservoir and even the building of reasonably-attractive walls in the gardens of potentially-affected properties. In fact, they did such a good job that the risk of flooding from the river is negligible for the foreseeable future.
Today, though, we pulled out of the purchase of the riverside house. Why? We commissioned a more detailed flood report after someone had set alarm bells ringing about the impact of climate change. To cut a long story short, the property is at high risk of surface water flooding, and (in our opinion) the Environment Agency’s river flood defences potentially exacerbate that risk.
The reason I wanted to note this, other than it being a significant event in my life, is to share what I’ve learned about cumulative risk. I also wanted to note how helpful ChatGPT 4 was at summarising and making calculations based on the report. It was quite technical in places and, while data is good, we needed to extract meaning.
At the end of the day, humans should make decisions. But having a very quick and technically-proficient assistant to pull out and interpret data is extraordinarily useful.
I used the AskYourPDF plugin for ChatGPT, beginning by asking it specifically to explain “in the simplest language possible” the risk from surface water flooding. I then asked if we were planning to live there for 20 years whether it would be a sensible purchase. While it wouldn’t make a specific recommendation, its responses erred on the side of caution.
Going further, I asked about the impact of climate change on the property, to which it responded about things we’d already considered (increased rainfall, urbanisation), and things we hadn’t (sea level rise, decreased snowfall). This gave us further pause for thought.
The next day, already thinking that this wouldn’t be a wise investment, I asked ChatGPT to “come up with a range of 5 personas and explain how they would approach a purchasing decision for this property.” I specifically asked it to include the notion of “risk appetite” as part of this. The results were interesting. I followed up by enquiring “If these personas talked to one another and had to make one decision based on their discussion, what would be that decision?” Somewhat predictably, the personas consensus view was not to go ahead with the purchase.
The next step was to use it to calculate cumulative risk, which we’d realised hadn’t been specified in the report. It’s been a while since I did this kind of Maths, and doing it manually is somewhat confusing to my brain. So I asked ChatGPT:
So a probability greater than a coin toss that, based on the current situation, the garden would be flooded. And this wasn’t taking into account other factors that weren’t covered by the data in the report.
The final step was to think about the risk of surface water flooding being so bad that it potentially enters the house. This was mentioned in the report as the ‘low-risk scenario’ of between 0.1% and 1% that up to 0.6m of water would be adjacent to the dwelling
So, even without the uncertainty of climate change, if we take the middle of the upper and lower bounds of cumulative risk, there’s a 1 in 10 chance that there will be up to 60cm of flood water adjacent to the property? No thanks.
Having pulled out of the purchase, this morning I’ve been to register our details with a bunch of estate agents for rentals. The chances are we’ll have to bide our time to get the exact house we want. That will be annoying, but not too much of a hardship. Especially as the next house we buy we’ll probably be staying in for a while.
![Thank you for providing access to the document again. Based on the extracted information:
- The property is shown to be located within an area of **High surface water flood risk**.
- The definitions for the risk levels are as follows:
- **High risk**: annual chance of flooding of greater than 3.3%.
- **Medium risk**: annual chance of flooding of between 1% and 3.3%.
- **Low risk**: annual chance of flooding of between 0.1% and 1%.
- **Very Low risk**: annual chance of flooding of less than 0.1%.
Given that the property is in the high-risk category, the upper bound annual flood risk for surface water flooding is 3.3%. However, you've also asked for calculations for 5%, 6%, and 7%. We've already provided the 20-year cumulative risk for 5%, so let's calculate for 6% and 7%:
For 6%:
\[ \text{Risk over 20 years} = 1 - (0.94)^{20} \]
\[ \text{Risk over 20 years} \approx 74.0% \]
For 7%:
\[ \text{Risk over 20 years} = 1 - (0.93)^{20} \]
\[ \text{Risk over 20 years} \approx 80.7% \]
So, to summarize:
- For a 3.3% annual risk, the 20-year cumulative risk is approximately 49.4%.
- For a 5% annual risk, the 20-year cumulative risk is approximately 64.2%.
- For a 6% annual risk, the 20-year cumulative risk is approximately 74.0%.
- For a 7% annual risk, the 20-year cumulative risk is approximately 80.7%.](https://dougbelshaw.com/blog/wp-content/uploads/2023/08/chatgpt-flood-risk.png)
![So if we stayed there for 20 years, what's the cumulative risk from the annual low risk scenario?
Given the range for the low-risk scenario is between 0.1% and 1%, let's calculate the cumulative risk over 20 years for both the lower and upper bounds of this range.
Using the formula:
\[ \text{Risk over period} = 1 - (1 - \text{annual risk})^{n} \]
1. **For the lower bound of 0.1% (0.001)**:
\[ \text{Risk over 20 years} = 1 - (0.999)^{20} \]
\[ \text{Risk over 20 years} \approx 2.0% \]
2. **For the upper bound of 1% (0.01)**:
\[ \text{Risk over 20 years} = 1 - (0.99)^{20} \]
\[ \text{Risk over 20 years} \approx 18.2% \]
So, for the low-risk scenario:
- Over a 20-year period, there's approximately a 2.0% cumulative risk at the lower bound (0.1% annual risk) and an 18.2% cumulative risk at the upper bound (1% annual risk) of the property experiencing a flooding event.](https://dougbelshaw.com/blog/wp-content/uploads/2023/08/chatgpt-flood-risk-2.png)
