Content
The Content is worth 35% of your module grade. The overall word limit for this assessment is 2,500 words. We will only count the text that you’ve added to the final PDF. Headings, guidance, etc. do no count towards the total. References do. Please tidy up the template before submitting (i.e. delete the ‘Code Examples’ section and any guidance that is not relevant (i.e. ‘Draft answer due…’ and the ‘Briefing’ section).
Set Questions
In the midst of an election, a newspaper has broken the story of an advisor on social mobility to the Mayor owning three homes, two of which are let on Airbnb (one of which is still council-owned housing!). The opposition has announced a plan to force all professional landlords to register their properties and face higher Council Tax rates claiming that Airbnb is ‘out of control’ in the capital.
The Mayor wants to understand the scale of the ‘problem’ and the likely impacts of the opposition’s proposal so that they can either adopt it (and show how responsive they are) or demonstrate how poorly thought-through the opposition’s proposal is (and show that they’re not ready to govern).
They have come to you—their team of data analysts and policy advisors—for a briefing supported by evidence and visualisations that they can use in their campaign communications. You are working in an information-poor environment, so you will need to make assumptions, justify them clearly, and show how they affect your conclusions. Use data, reasoning, and clear visualisation to build a persuasive and evidence-informed argument.
1. Is Airbnb ‘out of control’ in London?
Draft answer due Week 7.
2. How many professional landlords are there?
Draft answer due Week 8.
3. How many properties would be affected by the opposition’s proposal?
Draft answer due Week 9.
4. What are the likely pros and cons of the opposition’s proposal (for the Mayor, for residents, and for the city)?
Briefing Rubric
You are advising the Mayor on how to respond to a political scandal involving Airbnb and housing. You will work in an information-poor environment, meaning that you’ll need to make assumptions, justify them, and use creative reasoning to produce an evidence-informed and persuasive briefing.
Your task is to provide a short, well-evidenced briefing that answers the five set questions. You’ll be assessed not on finding the right answer (there isn’t one), but on how well you reason, justify, visualise, and communicate your analysis.
Marking Criteria
| Criterion | Weight | What we will look for |
|---|---|---|
| Analytical reasoning & use of data | 25% | How effectively, creatively, and defensibly you use data and assumptions to address the questions. Show that your analysis is logical and evidence-based, and that you understand the limits of your data. |
| Clarity and persuasiveness of argument | 25% | How clearly and convincingly you answer the five questions. Structure your argument logically, back up your points with evidence or reasoning, and show that you can weigh different perspectives. The goal is to brief a decision-maker, not write a long academic essay. |
| Visualisation and communication | 20% | How effectively you use charts, tables, or visuals to tell the story. Visuals should be clear, relevant, and easy to read. The writing should be concise, professional, and appropriate for the Mayor and a policy audience. |
| Policy and ethical insight | 20% | How well you understand the bigger picture — the political, ethical, and social dimensions of the issue. Who wins or loses from the proposal? What are the trade-offs or unintended consequences? Show awareness of housing and data justice issues. |
| Transparency and reflexivity | 10% | How openly and thoughtfully you discuss your assumptions, uncertainties, and limitations. Explain how confident you are in your findings and how your assumptions might shape your conclusions. |
Tips for Success
- Be creative, but stay realistic and justify the assumptions that you make, clearly explaining your reasoning.
- Your briefing feels professional and policy-ready, with visuals helping to strengthen your message. It looks like something the Mayor could actually use!
- Remember your audience: write for the Mayor, this is not a technical report.
- You show critical awareness of data gaps, politics, and ethics, and reflect honestly on uncertainty and what could be done better with more time or information.
- Think critically about ‘control’, ‘professional landlord’, and ‘social mobility’ because these are political ideas as much as analytical categories.
Additional Information
The briefing can be written without sophisticated modelling through the judicious use of descriptive statistics (see, for instance, Housing and Inequality in London and The suburbanisation of poverty in British cities, 2004-16: extent, processes and nature).
Students may use data from more than one time period if they wish, but this is not required. You can see the available data sets on Orca.
Style
This is not an essay, and students who submit answers using a traditional essay style will see their overall mark impacted as a result. You must preserve the question/response format, and your responses should be readily-grasped by an intelligent, but non-technical audience. This doesn’t mean that you don’t need citations, but you should not employ an academic writing style. See the examples provided below for insights into how to write for a less technical audience.
There will also be opportunities to discuss the submission during the second half of term.
What makes writing a good briefing hard—and not just about writing good code—is finding the right balance of technical detail and high-level explanation: you can’t just say ‘here are the five types of accommodation we found…’, but you also can’t say ‘we tested clustering solutions in the range 3–50 and found the optimal result at k=12…’
Figures & Tables
While figures and tables can help to illustrate a key point, students should give careful consideration to the trade-offs involved: more figures may serve to illustrate your points but cause the reader to lose the thread of your argument and negatively impact the presentation mark.
Unless you are presenting (and citing) a figure from another source as part of your framing, all figures and tables used must be generated by Python code cells included in the markdown file. You may not modify or create figures in another application since this undermines the reproducibility of the analysis.
Assumptions
It is highly likely that you will need to make substantial use of assumptions in developing your briefing for the Mayor. These should be plausible and, where possible, documented. For example (and using a randomly selected reference):
Based on Travers, Sims, and Bosetti (2016), we assume that the average visitor to London walks at a rate of 3m/s (180m/minute). We further assume that a 10-minute walk is reasonable, giving us a limit of 1,800m…
Or:
We assume that tourists spend approximately £X/day in their local area (see, e.g., Wachsmuth and Weisler 2018), implying that each property generates a maximum of £Y/year in local spending (assuming continuous occupation). In practice, we adopt the approach of XXX (2019) to estimate occupancy from reviews to generate a more realistic impact of…
So you can see that neither of these requires more than a couple of citations to allow you to estimate some reasonable threshold for a metric of interest. This will be a lot simpler than trying to look up global tourist spending information or TfL travel stats. Yes, it’s a rough-and-ready estimate, but it also doesn’t pull the number out of thin air.
Referencing
You will need to make use of BibTeX and Markdown referencing in Quarto. ‘Hard-coded’ references will not be considered.
Although you can create BibTeX entries by hand, you will probaly want to make use of BibDesk (Mac) or JabRef (Mac/Windows). Zotero shuould also work to edit the BibTeX file.
In Google Scholar, if you want to add a reference to your BibTeX file there’s an option in the Cite functionality to copy a BibTeX entry to the clipboard and then pasted this into BibDesk or JabRef.
Examples
Although the following examples are all much longer than permitted under the assessment format, they are exemplary in their communication of data and key findings in a manner that is clear, straightforward, and well-illustrated using maps, charts, and tables. So they can help you to think about how best to present information for non-expert audiences:
- Travers et al. (2016), Housing and Inequality in London, Centre for London; URL.
- Bivens, J. (2019), The economic costs and benefits of Airbnb, Economic Policy Institute; URL.
- Wachsmuth et al. (2018), The High Cost of Short-Term Rentals in New York City, Urban Politics and Governance research group, McGill University; URL.
Notice how these ‘models’ differ from a traditional essay format. So instead of Introduction, Literature, etc. you will see the evidence is developed in parallel with the background material. This format provides for more flexibility in style and presentation, though you will note that they all refer to a mix of academic and grey literature as well!
Partial Bibliography
You will also want to expand on the partial bibliography file provided. This is by no means complete and you will need to find relevant work, but it gives you a good starting point for using a BibTeX file.