Outline

Overview

Modern life is marked by profound economic and social inequality. This unit guides students into their own research on the dimensions, causes, and consequences of inequality, with a special focus on Sydney. Students will learn in a hands-on way, combining quantitative and qualitative approaches to social reality. They will learn practical skills in data visualisation with state-of-the-art software, and be asked to think creatively about responses to the processes reproducing inequality.

Unit details and rules

Academic unit	Political Economy
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Michael Beggs, michael.beggs@sydney.edu.au
Lecturer(s)	Amanda Elliot, amanda.elliot@sydney.edu.au
Lecturer(s)	Michael Beggs, michael.beggs@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Data visualisation report Construct and discuss a data visualisation of some aspect of inequality	30%	Formal exam period Due date: 18 Jun 2021 at 23:59	1500 words and graphic
Outcomes assessed:
Assignment	Quizzes Short-answer quizzes on unit content	20%	Multiple weeks	3 x 250 word
Outcomes assessed:
Assignment	Literature review Critically discuss the literature on an aspect of inequality in Australia	30%	Week 06 Due date: 16 Apr 2021 at 23:59	1500 words
Outcomes assessed:
Assignment	Peer review Comment constructively on a peer's literature review	20%	Week 08 Due date: 30 Apr 2021 at 23:59	750 words
Outcomes assessed:

Assessment summary

Literature review: Choose one aspect of inequality in Australia, which may involve trends, causes, consequences and/or policy. Summarise and critically discuss the scholarly and/or official (including government and NGO) literature on it.
Data visualisation report: Find a dataset on some quantitative aspect of inequality in Australia. Construct a visualisation (or a set of visualisations) that clearly presents something interesting about this data. This may include charts or maps. Write a report explaining the visualisation(s) and commenting on what is shown.
Peer review: Read and respond to a literature review from another member of the class. The point is not to critique the review, but to engage in a conversation. What do you find interesting and why? What would you add? Do you disagree with anything?
Quizzes: There will be three short answer quizzes over the semester, testing your understanding of important concepts and facts.

Assessment criteria

Result name	Mark range	Description
High Distinction	85-100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard
Distinction	75-84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard
Credit	65-74	Awarded when you demonstrate the learning outcomes for the unit at a good standard
Pass	50-64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard
Fail	0-49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	What is inequality and why do we care?	Seminar (2 hr)
Week 01	Setting up	Computer laboratory (1 hr)
Week 02	Dimensions of inequality: inequality of what? Of whom?	Seminar (2 hr)
Week 02	Looking at data: principles of visualisation	Computer laboratory (1 hr)
Week 03	Dimensions of inequality: Social, cultural and economic	Seminar (2 hr)
Week 03	Getting started with R	Computer laboratory (1 hr)
Week 04	Dimensions of inequality: Status and recognition	Seminar (2 hr)
Week 04	Data sources, cleaning your data	Computer laboratory (1 hr)
Week 05	Representing inequality: media, policy and politics on poverty and social inclusion	Seminar (2 hr)
Week 05	Making a plot: basics of ggplot	Computer laboratory (1 hr)
Week 06	Explaining inequality I: trends in functional distribution	Seminar (2 hr)
Week 06	Showing the right numbers	Computer laboratory (1 hr)
Week 07	Explaining inequality II: Labour market trends	Seminar (2 hr)
Week 07	More chart types	Computer laboratory (1 hr)
Week 08	Explaining inequality III: dynamics of wealth	Seminar (2 hr)
Week 08	Graph tables, add labels, make notes	Computer laboratory (1 hr)
Week 09	Consequences of inequality I: education	Seminar (2 hr)
Week 09	Maps	Computer laboratory (1 hr)
Week 10	Consequences of inequality II: health	Seminar (2 hr)
Week 10	Mapping inequality in Sydney and Australia	Computer laboratory (1 hr)
Week 11	Action I: Politics of inequality	Seminar (2 hr)
Week 11	Project workshop, troubleshooting	Computer laboratory (1 hr)
Week 12	Action II: Policies and practices	Seminar (2 hr)
Week 12	Project workshop, troubleshooting	Computer laboratory (1 hr)
Week 13	Conclusion and visualisation presentations	Seminar (2 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. demonstrate an understanding of the causes, distribution and implications of inequality for the social, political and economic well-being of Australia.
LO2. demonstrate an understanding of how issues of wealth, class, gender, ethnicity and indigeneity influence the opportunities and constraints faced by individuals and groups.
LO3. undertake analysis of official data sets (eg: ABS).
LO4. undertake the collection and analysis of primary data.
LO5. use data visualization tools to effectively communicate research findings for public impact.
LO6. demonstrate a capacity for respectful critical engagement with others.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This unit is being run for the first time in 2021.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

FASS6001: Dimensions of Inequality

Semester 1, 2021 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links