Welcome to Human Geography Fieldwork
Hello Geographer! Welcome to your revision guide for Human Geography Fieldwork. This chapter is part of the Geographical Skills including Fieldwork unit for OCR GCSE (9-1) Geography B (Geography for Enquiring Minds) - J384.
In your exam, human fieldwork is tested in Component 02: People and Society (Section B). Fieldwork questions account for roughly 15% of your overall GCSE grade, so mastering this topic can give your marks a significant boost! You will be asked about your own human fieldwork investigation as well as "unfamiliar" fieldwork examples set by the examiner.
1. The 6-Stage Geographical Enquiry Process
Whenever geographers step out into the real world to investigate a town, city, or village, they follow a structured 6-stage enquiry process. Think of this like a scientific recipe for solving a geographical puzzle!
Stage 1: Creating an Aim for Fieldwork
Every great investigation starts with a clear focus. You need to develop either a broad enquiry question (e.g., "How does environmental quality change from the CBD to the suburbs?") or a specific, testable hypothesis (e.g., "Environmental quality increases as distance from the town centre increases").
Stage 2: How Evidence is Collected
This is where you decide what data you need and how you will gather it. You choose your data types (primary vs secondary) and select a fair sampling method (such as random, systematic, or stratified).
Stage 3: Processing and Presenting Evidence
Once you return with raw data, you need to turn numbers and notes into clear visuals. This involves creating appropriate charts, graphs, or cartographic (map-based) techniques like land-use maps.
Stage 4: Analysing Evidence
In this stage, you look closely at your graphs and maps. What patterns do you see? Are there clear trends? Are there any odd results that don't fit the pattern (known as anomalies)? You must explain why these patterns exist.
Stage 5: Drawing Conclusions
Here, you directly answer your original enquiry question or state whether your hypothesis was supported or rejected. You must always back up your statements using specific data collected during your fieldwork.
Stage 6: Evaluation
A true geographer is honest about their work. You critically reflect on your methods: What were the limitations? Was the sample size big enough? How reliable was the data? What would you do differently next time?
Key Takeaway for Section 1: The 6 stages are: Aim \(\rightarrow\) Data Collection \(\rightarrow\) Presentation \(\rightarrow\) Analysis \(\rightarrow\) Conclusion \(\rightarrow\) Evaluation. Always keep these steps in order!
2. Data Collection: Types of Data
Don't worry if data terms sound confusing at first—they break down into two simple pairs:
Primary vs Secondary Data
Primary Data: Original data that you collect yourself first-hand out in the field.
Examples: Pedestrian tallies, your own questionnaire responses, photos you took, and Environmental Quality Surveys.
Secondary Data: Information that someone else has already collected and published, which you use to support your study.
Examples: Census data from the Office for National Statistics (ONS), historical maps of an urban area, and Environment Agency reports.
Quantitative vs Qualitative Data
Quantitative Data: Numerical data that can be counted, measured, and analysed statistically.
Examples: Number of pedestrians per minute, traffic counts, shop tallies.
Memory trick: Quantitative has a 't' for total / numbers.
Qualitative Data: Non-numerical, descriptive data that records opinions, qualities, or visual impressions.
Examples: Field sketches, interview transcripts, annotated photographs.
Memory trick: Qualitative focuses on the quality of a description or feeling.
Key Takeaway for Section 2: Primary = collected by you; Secondary = collected by others. Quantitative = numbers; Qualitative = descriptions and words.
3. Sampling Techniques
You cannot survey every single person or street in a city, so you must select a sample. OCR requires you to understand and justify three main sampling techniques:
A. Random Sampling
What is it? Every location or person has an entirely equal chance of being chosen.
How it is done: Using a random number generator to pick grid coordinates on a town map.
Advantage: It removes human bias because the researcher does not hand-pick the sites.
B. Systematic Sampling
What is it? Collecting data at regular, evenly spaced intervals.
How it is done: Stopping every \(50\text{ metres}\) along a street transect, or asking every \(5^{\text{th}}\) person who walks past.
Advantage: It provides an even and structured coverage across a whole study area.
C. Stratified Sampling
What is it? Dividing the population or area into distinct sub-groups (layers), and sampling proportionally from each group.
How it is done: If a town's population is \(60\%\) adults and \(40\%\) seniors, you ensure your questionnaire sample has the exact same split (\(60\%\) adults, \(40\%\) seniors).
Advantage: It ensures that smaller or minority groups are fairly represented and not left out.
Key Takeaway for Section 3: Random = equal chance (random numbers); Systematic = regular intervals (every \(n^{\text{th}}\) item); Stratified = split into proportional sub-groups.
4. Typical Human Fieldwork Methods & Indicators
For OCR B, human geography fieldwork often focuses on themes such as Urban Futures and Economic Hubs. Here are common methods you might use or see in the exam:
1. Land-Use Mapping (The RICEPOTS Classification)
Geographers map what different buildings are used for across an urban area using the RICEPOTS acronym:
• R – Residential (houses, flats)
• I – Industrial (factories, warehouses)
• C – Commercial (shops, banks)
• E – Entertainment (cinemas, restaurants)
• P – Public (libraries, town halls, hospitals)
• O – Open space (parks, recreation grounds)
• T – Transport (bus stations, car parks, train stations)
• S – Services (schools, doctors, post offices)
2. Environmental Quality Survey (EQS)
An EQS records human impressions of an urban environment. It commonly uses a Bipolar Scale (for example, ranging from \(-3\) to \(+3\)), where negative numbers reflect poor conditions and positive numbers reflect pleasant conditions:
• Heavy Litter (\(-3\)) \(\longleftrightarrow\) Spotless / No Litter (\(+3\))
• Noisy / High Traffic (\(-3\)) \(\longleftrightarrow\) Quiet / Peaceful (\(+3\))
• No Green Space (\(-3\)) \(\longleftrightarrow\) Abundant Green Space / Trees (\(+3\))
3. Pedestrian and Traffic Counts
Counting the number of people (footfall) or vehicles passing a point in a set time (e.g., \(5\text{ minutes}\)). This measures accessibility and helps identify the central economic core (CBD) of a town.
Key Takeaway for Section 4: Remember RICEPOTS for land-use mapping and Bipolar Scales (\(-3\) to \(+3\)) for Environmental Quality Surveys.
5. Essential Mathematical & Statistical Skills
Fieldwork requires you to manipulate and analyse your numbers. Make sure you are confident using these mathematical skills:
A. Central Tendency and Spread
• Mean: Add all values together and divide by the total number of values.
• Median: Put the values in order from smallest to largest and find the middle number.
• Mode: The most frequently occurring value in the dataset.
• Range: The difference between the highest and lowest value (\(\text{Highest} - \text{Lowest}\)).
B. Interquartile Range (IQR)
The Interquartile Range measures the spread of the middle \(50\%\) of your data, ignoring extreme outliers. It is calculated by finding the difference between the Upper Quartile (\(Q_3\)) and the Lower Quartile (\(Q_1\)):
\(\text{IQR} = Q_3 - Q_1\)
C. Percentage Change Formula
To calculate how much footfall or traffic has increased or decreased between two locations or time periods, use the percentage change formula:
\(\text{Percentage Change} = \left( \frac{\text{New Value} - \text{Old Value}}{\text{Old Value}} \right) \times 100\)
Example: If footfall in the high street was \(120\) people per hour in the morning and rose to \(150\) people per hour in the afternoon:
\(\text{Percentage Change} = \left( \frac{150 - 120}{120} \right) \times 100 = \left( \frac{30}{120} \right) \times 100 = 25\%\) increase.
Key Takeaway for Section 5: Learn the percentage change formula by heart: \(\left( \frac{\text{Difference}}{\text{Original}} \right) \times 100\).
6. Common Exam Pitfalls & How to Avoid Them
OCR examiners frequently highlight the same student mistakes in Component 02, Section B. Use these tips to ensure you secure top marks:
1. Describing vs Justifying
• Common Mistake: Simply writing what you did ("We stood on the corner and used a tally chart to count pedestrians.").
• Top-Mark Approach: Justify why that method was chosen for your aim ("A 5-minute tally chart was chosen because it provided quick, comparable quantitative data to show footfall variations between the CBD and suburbs.").
2. Vague Evaluations
• Common Mistake: Writing vague statements like "We might have made mistakes" or "Someone counted wrong."
• Top-Mark Approach: State a specific limitation and a precise improvement ("Sampling footfall solely on a Wednesday morning gave an unrepresentative view of shopping patterns. To improve reliability, we should repeat the count at the same time on a Saturday afternoon.").
3. Hypothesis Mismatch
• Common Mistake: Writing a conclusion about the area without directly addressing the starting hypothesis.
• Top-Mark Approach: State clearly whether the hypothesis was supported, partially supported, or rejected, and quote specific evidence to prove it.
4. Confusing Sampling Terms
• Common Mistake: Saying you chose people "at random" when you actually stopped every \(5^{\text{th}}\) person (which is systematic).
5. Incomplete Comparisons
• Common Mistake: Listing data for Site A, then listing data for Site B separately without linking them.
• Top-Mark Approach: Use comparative connectives such as whereas, alternatively, or significantly higher than ("Site 1 had an EQS score of \(+14\), whereas Site 4 scored only \(-5\), showing a marked decline in environmental quality.").
Quick Revision Checklist
• Can you name the 6 stages of the enquiry process in order?
• Can you explain the difference between primary and secondary data?
• Can you identify and justify random, systematic, and stratified sampling?
• What does each letter in RICEPOTS stand for?
• How does a bipolar scale work on an EQS (\(-3\) to \(+3\))?
• Can you calculate mean, median, mode, range, IQR, and percentage change?