IA - Student Guide
Introduction
This pages provides the assessment criteria and a step by step student guideline for students to use whilst writing their internal assessment. The guideline contains a useful checklist for students that runs them through the structure of the written report.
Essential Information
Students should produce one written report. The report must not exceed 2,500 words.
You must not exceed the word limit
The following are not included in the word count:
- Title page
- Acknowledgments
- Contents page
- Titles and subtitles
- References
- Footnotes—up to a maximum of 15 words each
- Map legends and/or keys
- Labels—of 10 words or less
- Tables—of statistical or numerical data, or categories, classes or group names
- Calculations
- Appendices—containing only raw data and/or calculations
Everything else is included in the word count, as well as all annotations over 10 words and any footnotes over 15 words.
If you do exceed the word limit:
Moderators are advised to stop reading if you exceed the word count and you will lose marks for the components written beyond the word limit.
Emphasis
Most marks are allocated for the treatment and analysis of information. Each investigation must be focused around an analytical structure that develops an argument on the fieldwork question by addressing the aims or hypotheses. You must avoid over descriptive or over theorized introductions.
Format of the report
The fieldwork written report must meet the following requirements of organization and presentation.
- 2,500-word limit.
- Presentation is well structured, pages are numbered.
- Illustrative material is fully integrated into the body of the report and is not dumped in the appendix.
- Maps, diagrams and tables are numbered and referenced in the text.
- References used for background information follow standard conventions. (Guidance is shown below)
Students should format their written reports based aon the formal criteria for marking. The following table shows the IB suggested format:
Report section | Criterion | Marks allocated out of 25 | Suggested word limit |
---|---|---|---|
Fieldwork question and geographic context | A | 3 | 300 |
Method(s) of investigation | B | 3 | 300 |
Quality and treatment of information collected and written analysis (integrated) | C | 6 | 500 |
Written analysis | D | 8 | 850 |
Conclusion | E | 2 | 200 |
Evaluation | F | 3 | 300 |
Total | 25 | 2,450 |
Source: IB Geography Internal Assessment Guide
Please note these are only suggested word limits and there is flexibility. However written reports should match up with the weighting of marks available for each criteria
How to structure your introduction
Sample Methods
It’s impossible to measure the entire area under study. It’s important that you sample the area.
In reality there is simply not enough; time, people, equipment, or access to suitable sites to measure every. Therefore an appropriate sampling strategy is adopted to obtain a representative, and statistically valid sample of the whole. There are three main sample methods:
- Random
- Systematic
- Stratified
Random Sample Method
The random sample method is the least biased of all sampling techniques, there is no subjectivity - each member of the total population has an equal chance of being selected
It can be obtained using random number tables, e.g. create a grid of the area you want to cover give each square a number and then draw the square like a raffle.
Systematic sample Method
Samples are chosen in a systematic, or regular way.
They are evenly/regularly distributed in a spatial context, for example every 10 metes along a transect line (town, river or coastal surveys)
They can be at equal/regular intervals in a temporal context, for example every half hour or at set times of the day (weather)
They can be regularly numbered, for example every tenth house or person
Stratified Sample Method
.
This method is used when the parent population or area is made up of different subsets. These sub-sets make up different proportions of the total, and therefore sampling should be stratified to ensure that results are proportional and representative of the whole. In the example below shrubby clearing represents only 10% of the area and so should only be 10% of the sample.
You should definitely consider stratified sampling when conducting population surveys
The role of hypotheses
A hypothesis is a proposed explanation made on the basis of limited evidence as a starting point for further investigation. Generally it is a positive statement which can can then be tested through the collection, interpretation and analysis of a larger amount of information.
A null hypothesis can also be used when looking at relationships between two sets of data or groups. the null hypothesis usually refers to a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.
The hypotheses may increase in complexity as the investigation continues. It is a good idea that the last hypothesis integrates more of the data so students can develop the connections across their data
Criterion A - Fieldwork Question and Geographic Context (300)
Assessment Criteria
To achieve 3/3 Students should meet the following assessment criteria:
The fieldwork question is well focused with a detailed, accurate explanation of the geographic context and is related to the syllabus. A good locational map is presented.
Student should include the following:
A narrowly focused fieldwork question
This should be based on a local scale and require the collection of primary data to interpret and analyze.
A student prediction
This can be based around hypotheses or sub-aims and should be supported by the relevant theoretical context. After all your prediction is based on a core of knowledge. This also links well to the geographical context
The geographical context
This explains why and where the fieldwork investigation is carried out. This can include relevant socio-economic conditions and place context. It may draw on spatial and physical characteristics, as well as key concepts and relevant theory.
A map of the research area
A map to show the situation of the research area and/or the locations of sites and zones used in the fieldwork.
The map must be made by the students and internet maps avoided. Sketch maps are ideal and should include a frame, north arrow and scale.
Link to the Syllabus
Students must also state the area(s) of the syllabus to which the study relates. This can should be integrated into the theoretical context of the introduction and mustn't be a screen shot of the syllabus.
Exemplary Work
Students can consider presenting the introduction in the following way:
To what extent does the upper course of the River Ninglinspo in Belgium correspond to the Bradshaw Model
Geographic context:
We decided to study the River Ninglinspo because it's the only mountain river in Belgium, it's easily accessible and is located relatively close to our school so that we could reach it and complete our investigation in one day.
The River Ninglinspo is located in the Belgian Ardennes 30km south of Liege. We identified 8 sites downstream starting close to the source and finishing close to it confluence with the River Ambleve. Its location can be seen in figure 1.0 below
To focus the investigation three hypotheses have been established. These include:
- The cross sectional area of the river will increase downstream
- River discharge will increase downstream
- Local channel factors will be a major influencing factor on velocity
These three hypotheses refer to at least 4 of the factors featured in Bradshaw's Model, shown in figure 1.1
I would expect to the first two hypotheses to prove correct because as we can see from the model both channel width and depth increase and discharge is one of the largest increasing characteristics. This is because as a river flows downstream effectively its drainage area increases in size and more water flows into the river from the surrounding catchment and tributaries. This increase in water in turn increases the depth, width and discharge of the river. Remembering the limitations of models I would expect local channel characteristics such as bedload and channel shape and human factors to influence velocity.
Link to Syllabus
This study relates to subsection from drainage basin and flooding in the Freshwater topic. the requirement is to define stream discharge and to examine its relationship to stream flow and channel shape.
Introducing the Methodology
A good rule of thumb for students to think about when writing their methodology follows the question. Could your grandparents repeat the investigation based on your description.
The methodology should include a description of the study design, choice of survey sites and/or zones and transects. In addition, the sampling methods used to identify the survey sites. A map may be useful to show this or students can refer back to the map that they used in the introduction.
Students should then write a description of the methods, including tables of data, surveys and fieldwork. It's possible to use diagram and annotated photograph and/or sketches to illustrate the methods.
Finally students should justify their choice of method by explaining how the method and sample method enabled them to collect reliable and representative information from the field.
In order to save on word count a table can be used.
Method | Equipment | Description | Diagram | Justification |
---|---|---|---|---|
Recording depth |
| Use the ranging poles for perpendicular cross section of the river. Measure the width with a tort tape measure. Divide the width by 5 and measure the depth at two banks and the four equidistant points with a meter rule avoiding any interference | The ranging poles and tort tape measure ensure an accurate cross section. The equidistant points are systematic sample of depth and improves consistency and speed |
Criterion B - Method(s) of investigation (300)
Assessment Criteria
To achieve 3/3 Students should meet the following assessment criteria:
There is a clear description and justification of the method(s) used for information collection. The method(s) used are well suited to the investigation of the fieldwork question
Students should include the following:
A general overview
The description may include the time, location and circumstances e.g. group or independent collection.
Reference to sample methods
These can be systematic, stratified or random and relate to how you sampled the available data at your survey site(s).
Description of methods
The way you collected your primary information must be described accurately. Could it be repeated independently from your description? Sampling can also be integrated with this.
This can be presented in a table but doesn't need to be and annotated diagrams and/or photos can provide additional support.
Justification of methods
The method(s) used must be justified. This includes clear reference to how the chosen method(s) allowed for the collection of sufficient and reliable primary information.
Presentation techniques
The following examples are all taken from successful internal assessments written by students at my school. .
A Location map of the River Lesse, showing both the location of survey sites and characteristics of the drainage basin
A Choropleth Map showing Environmental Quality
Choropleth uses colour to represent a range of data
It provides the important spatial element to the investigation
It allows easy comparison of zones.
The range needs to be chosen carefully
A Cluster Map Showing Location of Ethnic and High Street Orientated Functions
Cluster maps are effective layers of data and can also be used as an overlay with a choropleth map.
Clusters show general trends of spatial patterns
Cluster maps complement the statistical technique, nearest neighbour.
An Urban Transect showing Ground floor Land use
Transect use choropleth to distinguish ground floor land use
They are drawn to scale and show the spatial trend
Link well with a chosen sample method
Can be be combined with pie chart as well as annotated
A Composite Bar Graph Showing Environmental Quality at Different Sites
Composite bar graphs show comparison across a broad range of data
They present data effectively and are eay to read
A Composite Bar Graph on Environmental Quality Along a Transect
In this case the composite graph is comparing the CB with an area of the inner city
A Radar Chart comparing Environmental Quality in Two Zones
Radar charts are impressive to look and effective for showing a range of scores.
can be used to show congestion at different times of the day as well
Good for comparing different sets of data
An Radar Chart Based on a Survey
In this case the radar chart is used to present the results of population survey where a numerical scoring system has been used
Line Graphs to Show Bipolar Survey
A simple line depicts a bipolar survey based around the perception of place in this case.
It's easy to read and ane effective technique
Cross Sectional Graphs of a River with Velocity
Cross sectional graphs show channel width, depth, cross sectional area and velocity in one technique
Excellent for comparing changing patterns across sites
Good when combined with annotated photographs of sites
Long Profile (30 meters) Choropleth to Show Surface Velocity
This technique shows a a 30 meter long profile collected at one site with three working groups.
It's good to show how channel characteristics change at a local scale
When combined with annotation and/or a photograph it;s an excellent technique for explaining local channel factors
this graph can also be used an overlay on Google Earth
Line Graph to Show Hydraulic Radius
Simple graph, effective and easy to read
Line Graph to Show Average Velocity with Trend Line
Trend lines are useful when the line graph pattern shows significant variation
Annotated Photograph of a Survey Site
Annotated photographs and field sketches are very useful for setting the geographic context and interpreting how local factors have a influence
Criterion C - Quality and treatment of information (presentation) (1350)
- Criterion C is integrated with Criterion D in the written report
Assessment Criteria
To achieve 6/6 Students should meet the following assessment criteria:
The information collected is directly relevant to the fieldwork question and is sufficient in quantity and quality to allow for in‑depth analysis. The most appropriate techniques have been used effectively for both the treatment and display of information collected.
Students should include the following:
Display of information (6-10 examples)
Students should treat and display the information collected using the most appropriate and effective techniques. This may include tables of data, graphs, diagrams, maps, annotated photographs and images, matrices and field sketches and statistical tests (including confidence limits).
Full attention should be given to the accuracy of display, with titles, axis titles and integration
How to structure the data presentation
This is an important stage of the written report as it forms the basis of the analysis and is essential to the student's interpretation of information and argument. It is integrated with the analysis section of the report.
Students should consider a variety of effective techniques including graphs, tables, maps, sketch photographs and field sketches. The report is best structured in the same order as the hypotheses or subaims were stated in the introduction.
Students should use the hypotheses or subaims as subheadings within the report to inform the reader of how the presentation and analysis relates to the main fieldwork question.
Students should begin by providing the data in simple tables and graphs. Where appropriate the display of data can then become more precise and sophisticated.
For example, a student might first present a simple set of data on average channel depth in a table or graph. But this can then be followed up with a series of cross profile diagrams that show how depth varies across the channel. An annotated photograph or sketch diagram then shows the true nature of the river channel in terms of the influencing human and physical factors at the survey site.
The hypotheses may increase in complexity as the investigation continues. It is a good idea that the last hypothesis integrates more of the data so students can develop the connections across their data.
Returning to the river study the final hypothesis might refer to the changing discharge down stream as this factors connects channel depth, width, velocity and channel shape and roughness. In this way many connections and relationships can be interpreted.
Introducing the analysis
It is important that students understand how to structure and build up an argument within their presentation and analysis.
Data presentation and analysis
To what extent does the upper course of the River Lesse confirm Bradshaw's Model of channel processes?
Hypotheses: Average velocity increases downstream
The following data, shown in figure 3.0 reveals the pattern of changing average velocity downstream in a twenty kilometre section of the upper course of the River Lesse. The line shows a clear trend.
As can be seen in the general trend line, average velocity increases from sites 1 to 6, from 0.1 m/s to 0.5m/s, confirming the hypothesis that velocity should increase down stream. Bradshaw's Model also indicates that average velocity should increase downstream.
There is however significant variation in the trend, with average velocity showing variation both down the long
profile as well as between three cross profiles at each survey site.
Site 3a has significantly higher velocity compared to 2c and 3b and 3c. The latter two sets being located at the same survey site. This suggest that local channel factors play an important role in influencing average velocity. Furthermore,average velocity at 3a is only exceeded at sites 6b and 6c in the latter stage of the investigation. This trend suggests that average velocity is more dynamic in its downstream flow than Bradshaw's model suggests and that the hypothesis, whilst broadly accepted is subject to significant spatial variation.
This variation is illustrated in figures 3.1 and 3.3 below:
Figure 3.1. Cross Profile Velocity
Figure 3.1 shows effectively how velocity varies across the cross profile of three consecutive survey sites so that easy comparison can be made. As can be seen velocity is fastest in central points of the channel away from the bank and bed. The velocity also increases as depth of the river channel increases, as shown in 2b. Depth however is not the only factor influencing velocity. Figure 3.2 below shows an image of site 3b and highlights some of the local channel factors, including channel roughness and vegetation that might also influence average velocity.
Figure 3.2: Local Channel Factors
These channel factors such as bedload size, channel roughness and bed and bank vegetation all influence the efficiency of flow and ultimately average velocity. With increased channel roughness there is greater friction on the flow and so higher hydraulic radius. Therefore the river has reduced efficiency and lower velocity. In smooth section of river like that sown in figure 3.2, velocity is likely to be faster.
Figure 3.3 shows how velocity varies downstream within a 30 meter long profile of the river collected by three working groups
Figure 3.3: 30 Meter long profile, cross sectional area and velocity
As can be seen in the figure velocity is fastest at site 3a and falls through sites 3b and 3c. In this case channel shape is an influential factors. The channel becomes more narrow and constricted downstream form 3a and the impact is one of falling velocity.
In conclusion, the hypothesis that average velocity increases downstream is broadly accepted; the general trend in the study area confirms this. However, as my earlier prediction in the introduction suggested far more complexity is present and there is significant variation both in cross profile sections and long profile patterns explained by local channel characteristics. In the context of the River Lesse, Bradshaw's model seems too simplistic but yet the data does confirm the central trend that average velocity increases downstream.
Criterion D - Written analysis (1350)
- Criterion D is integrated with Criterion C in the written report
Assessment Criteria
To achieve 5-6 marks students should meet the following assessment criteria:
The report reveals a good level of knowledge and understanding. There is a well-reasoned, detailed analysis of the results with references to the fieldwork question, geographic context, information collected and illustrative material. There is an attempt to explain any anomalies in results.
To achieve 7-8 marks students should meet the following assessment criteria:
The report reveals a very good level of knowledge and understanding. There is a clear and well‑reasoned, detailed analysis of the results with strong references to the fieldwork question, geographic context, information collected and illustrative material. The attempt to explain any anomalies in results is good
Knowledge and Understanding of the fieldwork
Students should include the following:
Students interpret and explain the information in relation to the fieldwork question. This includes:
- describing trends and spatial patterns
- identifying and explaining any anomalies through reference to geographic context
- linking back to the theoretical context, aims and hypotheses
- justifying the presentation techniques chosen
How to Structure the Data Analysis
This is the most important stage in the written report and is integrated with the data presentation. The analysis should build a structured argument based on the field work question. But as explained earlier it is best to be broken up into more manageable chunks focused on answering the hypotheses and/or subaims. When addressing a hypothesis or subaim the report should also make clear links to the overall fieldwork question.
The analysis replicates the structure of the data presentation and so begins by describing the general trends in the data. A simple graph can be integrated with a simple overview of the general trend. Students should use data in their description and can where possible show more in depth sophisticated analysis. What is the trend, what is the distribution, what is the line of best fit and are their any important relationships or anomalies? Students should also consider explaining anomalies with reference to the geographic context.
If it's appropriate to look deeper at aspects of the data, then this should be attempted. This is shown in the exemplary material above. In this case the student develops the local channel characteristics to explain spatial variation that challenges the theoretical assumptions of the Bradshaw model. Similar approaches can be developed to explain spatial patterns in other geographical contexts.
The discussion should also make clear links to theory as well as the student's earlier predictions from their introduction. It is unlikely the theoretical model can be blindly accepted, the geographical context of the investigation should be very present in the student's analysis and if anything should be the more dominant influencing factor.
Statistical Techniques
It is very likely that as part of the written report students should make use of a range of different statistical techniques.
These include:
- using appropriate measures of central tendency, spread and cumulative frequency (median, mean, range, quartiles and inter-quartile range, mode and modal class)
- calculating percentage increase or decrease and understand the use of percentiles
- describing relationships in bivariate data: sketch trend lines through scatter plots, draw estimated lines of best fit, make predictions, interpolate and extrapolate trends
- being able to identify weaknesses in selective statistical presentation of data
- using statistical techniques such Spearman's Rank, Nearest Neighbour analysis, Chi Square or Mann Whitney
Measures of Central Tendency
Mean, median and mode
Interquartile Ranges
Standard Deviation
Standard deviation is a statistical technique that investigates how closely a set of data is clustered around the mean. When the sizes are tightly clustered and the distribution curve is steep, the standard deviation is small. When the sizes are spread apart and the distribution curve is relatively flat, the standard deviation is relatively large.
Standard Deviation follows the bell shaped curve with 68% of a distribution clustering within one standard deviation of the mean, 95% of the distribution within 2 stand deviations of the mean and 99.7% of the distribution clustering within 3 standard deviations.
Interpreting Scatter Graphs
Mann Whitney U Test
The Mann-Whitney U-test is used to test whether two independent samples of observations are drawn from the same or identical distributions
This example deals with two sets of sample data from two contrasting seismicly active regions, with the aim of comparing them and demonstrating differences. There are eight pairs of data in this example.
Source: AQA
Tests of significance are used to tell us whether the differences between the two sets of sample data are truly significant or whether these differences could have occurred by chance. Tests of significance tell us the probability level that magnitude of seismic activity between the two regions is due to chance.
Japan (A) | Italy (B) |
7.9 10 7.4 10 7.2 10 7 10 7 10 6.9 9.5 6.9 9.5 6.9 9.5 6.6 9 6.6 9 96.5 | 6.9 2 + 0.5 + 0.5+ 0.5 = 3.5 6.3 0 6.2 0 6 0 5.6 0 5.6 0 5.6 0 5.2 0 5.2 0 5 0 3.5 |
Spearman's Rank Coefficient
The Spearman's Rank Correlation Coefficient is used to measure the strength of a relationship between two sets of data.
Nearest Neighbour Analysis
Nearest neigbbour analysis is a statistical technique that looks to identify patterns in the distribution of factors within a site. It attempts to measure the distribution according to whether they are clustered, random or regular. Nearest neighbour analysis has good apllication in both urban environments for example a certain type of function as well as in environment stduies for example a certain type of flora in a woodland.
The nearest neighbour formula will produce a result between 0 and 2.15.
Formula
Key
nearest neighbour value | |
mean observed nearest neighbour distance | |
area under study | |
total number of points |
Steps
1. Select an area or zone of a certain size. In an urban area this may be a zone within the inner city or in a physical environment it might be an area of woodland
2. Within the given area measure the distance between one factor and its nearest neighbour. For example the distance between one Oak tree and its nearest oak. Or alternatively in an urban environment, one gentrified building in the inner city and another.
3. Apply the formula
The following example of a formula is taken from the Barcelona Field Centre study of pine trees
Example using a 20 x 20m quadrat with 18 trees:
Tree No. | Distance to nearest neighbour (m) |
1 | 4.10 |
2 | 5.75 |
3 | 3.00 |
4 | 3.80 |
5 | 3.58 |
6 | 3.12 |
7 | 2.20 |
8 | 2.20 |
9 | 3.87 |
10 | 2.40 |
11 | 2.40 |
12 | 3.75 |
13 | 4.20 |
14 | 1.83 |
15 | 3.10 |
16 | 0.98 |
17 | 0.98 |
18 | 2.51 |
Total | 53.77 |
2.99 | |
400m² | |
1.27 |
Criterion E - Conclusion (200)
Assessment Criteria
To achieve 2/2 marks students should meet the following assessment criteria:
There is a clear conclusion to the fieldwork question, consistent with the analysis
Students should include the following:
A summary of the main findings
A good structure to follow here would be to base your conclusions on sub-aims and hypotheses. Refer to the key (data) information as part of this.
A statement on the fieldwork question
There should be a clear, concise statement answering the fieldwork question.
Briefly explain conclusion
It is acceptable for the conclusion to state that the findings do not match the student’s earlier prediction and theoretical context. The geographic context might be briefly referred to to explain findings.
Criterion F - Evaluation (300)
Assessment Criteria
To achieve 3/3 marks students should meet the following assessment criteria:
Methods of collecting fieldwork information have been evaluated clearly. There are valid and realistic recommendations for improvements or extensions. There may be some suggestions for modifying the fieldwork question
Students should include the following:
Review the methodology
Students should review their methodology, including methods of collecting primary information. Within this, they should consider any factors that either improved or limited the validity of the data. How was personal bias avoided or not and what other factors such as weather or time were limiting factors.
Improving the investigation
Students should suggest realistic ways that the investigation could have been improved and ways it could be extended in the future.
Referencing
The IB stipulates that all secondary information must be referenced, using a standard author–date system, such as the Harvard system. This includes information from the internet, where references should include titles, URL addresses and dates when sites were visited. All sources of secondary information must be referenced. Footnotes may be used to reference material and, provided that these are brief, up to 15 words as noted below will not be included in the word count.
The Harvard System
For books, record:
- The author’s or editor’s name (or names)
- The year the book was published
- The title of the book
- If it is an edition other than the first
- The city the book was published in
- The name of the publisher
For journal articles record:
- The author’s name or names
- The year in which the journal was published
- The title of the article
- The title of the journal
- The page number/s of the article in the journal
- As much other information as you can find about the journal, for example the volume and issue numbers
For electronic resources, try to collect the information on the left if it is available, but also record:
- The date you accessed the source
- The electronic address or email
- The type of electronic resource (email, discussion forum, WWW page, etc)
Exeter University provides the following guidance for:
Book with one author
Adair, J. (1988) Effective time management: How to save time and spend it wisely, London: Pan Books.
Book with two authors
McCarthy, P. and Hatcher, C. (1996) Speaking persuasively: Making the most of your presentations, Sydney: Allen and Unwin.
Book with three or more authors
Fisher, R., Ury, W. and Patton, B. (1991) Getting to yes: Negotiating an agreement without giving in, 2^{nd} edition, London: Century Business.
Book – second or later edition
Barnes, R. (1995) Successful study for degrees, 2^{nd} edition, London: Routledge.
Book by same author in the same year
Napier, A. (1993a) Fatal storm, Sydney: Allen and Unwin.
Napier, A. (1993b) Survival at sea, Sydney: Allen and Unwin.
Book with an editor
Danaher, P. (ed.) (1998) Beyond the ferris wheel, Rockhampton: CQU Press.
If you have used a chapter in a book written by someone other than the editor
Byrne, J. (1995) ‘Disabilities in tertiary education’, in Rowan, L. and McNamee, J. (ed.) Voices of a Margin, Rockhampton: CQU Press.
Books with an anonymous or unknown author
The University Encyclopedia (1985) London: Roydon.
Electronic and web based sources
Journal article from CD-ROM, electronic database, or journal
Skargren, E.I. & Oberg, B. (1998) ‘Predictive factors for 1-year outcome of low-back and neck pain in patients treated in primary care: Comparison between the treatment strategies chiropractic and physiotherapy’, Pain [Electronic], vol. 77, no. 2, pp. 201-208, Available: Elsevier/ScienceDirect/ O304-3959(98)00101-8, [8 Feb 1999].
Other electronic sources
Electronic mail (e-mail)
Johnston, R. (2001) Access courses for women, e-mail to NIACE Lifelong Learning Mailing List (lifelong-learning@niace.org.uk), 22 Aug. [24 Aug 2001].
OR
Robinson, T. (2001) Re: Information on course structure, e-mail to S. Dhann (s.dhann@exeter.ac.uk), 12 Jul. [13 Jul 2001].
Discussion list
Berkowitz, P. (1995) April 3, ‘Sussy’s gravestone’, Mark Twain Forum [Online], 3 Apr, Available e-mail: TWAIN-L@yorkvm2.bitnet [3 Apr 1995].
World Wide Web page
Young, C. (2001) English Heritage position statement on the Valletta Convention, [Online], Available: //www.archaeol.freeuk.com/EHPostionStatement.htm [24 Aug 2001].