Cambridge IGCSE Global Perspectives (0457): Topic: Employment – Practice Questions

These are original questions written for Marlbridge, for revision and practice on this content. They are not reproduced past-paper questions, and they do not replicate the exam’s exact structure, question count or mark tariffs – examination boards hold copyright in their own papers. Use these alongside the official past papers from your board or school.

This set follows the Cambridge IGCSE Global Perspectives (0457) syllabus for examination in 2025, 2026 and 2027, Version 2 (published April 2025). It uses Employment, from the section 3 topic list, to practise the skills in section 2 and section 4. Questions 1-9 are source-based, in the style the syllabus describes for Component 1 Written Exam. Questions 10 and 11 are planning tasks for Component 2 Individual Report and Component 3 Team Project.

Topic knowledge is not assessed in 0457. Answer the source-based questions from the sources only. Velmora, its people, organisations and all figures are fictional.

Learn the skills first in the Employment study guide and the Employment revision notes. The 0457 course hub and the 0457 checklist show the whole course. For more general skills practice, try the Written Exam practice.

Questions

Source A – original text written for Marlbridge. Blog post by Amira, 22, a food-delivery rider in Selbury, Velmora (fictional).

Last week I worked 52 hours on the app and earned 410 velos before fuel, which cost me 62 velos. The national minimum wage is 9.50 velos an hour, but riders are classed as self-employed, so it does not apply to us. I like choosing my own hours because I study in the mornings. But when I was ill for a week in March, I earned nothing. Honestly, the app treats riders unfairly. Everyone I know at the depot would take a proper contract tomorrow.

Source B – original data written for Marlbridge (fictional). Velmora: youth unemployment rate (% of 15-24-year-olds in the labour force) and informal work (% of employed 15-24-year-olds with no contract).

Region	Unemployment 2019	Unemployment 2025	Informal work 2019	Informal work 2025
North (port region)	14.2	21.6	38	46
Central (includes Selbury)	11.8	12.4	22	25
South (farming region)	18.5	17.9	61	63

Source C – original text written for Marlbridge. Press release from the Velmora Employers’ Forum (fictional).

We invited all 1,200 member firms to an online survey and 96 replied. Of these, 70 (72.9%) agreed that “young applicants lack basic workplace skills”. Schools are clearly failing young people. The government should fund a national workplace-skills programme so that employers no longer carry this burden.

Source D – original text written for Marlbridge. Two views on automation at the Port of Kessin, in Velmora’s North (fictional).

Joel Marr, dockworkers’ union: “Every crane that drives itself takes bread from a family’s table. Since the automated terminal opened in 2021, youth unemployment in the North has soared. The government must ban further automation until every dock worker has a new job. Everyone knows robots only make the rich richer.”

Daria Venn, Minister for Industry: “Ports that refuse to automate lose ships to rival ports abroad. Kessin handled 18% more containers in 2025 than in 2020. Our retraining fund has already placed 640 former dock workers in new roles, and the port operator predicts 300 new technical jobs by 2028. Countries that resist technology always fall behind.”

Source E – original text written for Marlbridge. Options from Velmora’s Youth Employment Commission (fictional).

Action 1 – Wage subsidy. The government pays 40% of the minimum wage for 12 months for each new worker aged 16-24 hired. 15,000 places; cost about 119 million velos a year. Action 2 – Port Skills Apprenticeships. Two-year apprenticeships in the North in crane maintenance, logistics software and electrical work, co-funded by the port operator. 400 places a year. Action 3 – Rights for app workers. Extend the minimum wage and sick pay to app-based workers. App companies warn that delivery fees would rise and some riders could lose work.

1. Using Source A, identify one fact and one opinion. [2]

2. Using Source A, calculate Amira’s hourly earnings before fuel and after fuel, and state whether either meets the minimum wage. [3]

3. Using Source B:

(a) Identify the region with the largest rise in youth unemployment and give the change in percentage points. [2] (b) Joel Marr (Source D) says youth unemployment in the North “has soared” since the automated terminal opened. Explain two reasons why Source B does not prove that automation caused this rise. [4]

4. Using Source D:

(a) Identify one prediction. [1] (b) Identify one generalisation and explain why it weakens the argument. [2]

5. Using Sources A and E, explain two different perspectives on app-based work and why they differ. [6]

6. Using the sources:

(a) Explain two causes of youth unemployment in Velmora. [4] (b) Explain one consequence at a personal level and one at a national level. [4]

7. Using Source C:

(a) Evaluate the evidence for the claim that “schools are failing young people”. [8] (b) Suggest how you could research the claim that young applicants lack workplace skills. [6]

8. Evaluate the arguments of Joel Marr and Daria Venn in Source D. Which argument is stronger? [12]

9. Which action in Source E would be most effective in reducing youth unemployment in Velmora? Explain your judgement with reasons and evidence from all the sources. [16]

10. You are planning an Individual Report on Employment.

(a) Write a global research question that divides opinion. [2] (b) Identify one local or national perspective and one global perspective you would research, and a suitable source for each. [4]

11. Your Team Project team has found that few students in your school know about local apprenticeships.

(a) Suggest one action and how you would measure its success. [3] (b) Explain how a team of three could divide the research. [3]

Answers

The [1] points are a revision aid. The real exam and coursework mark extended answers with levels of response, best fit, not point by point.

1. Fact: “I worked 52 hours on the app and earned 410 velos” (it can be checked against app records) [1]. Opinion: “the app treats riders unfairly” (a personal judgement) [1]. [2] Examiner insight: quote the exact words; “she has a bad job” is your summary, not an opinion identified in the source.

2. Before fuel: 410 / 52 = 7.88 velos an hour [1]. After fuel: (410 - 62) / 52 = 6.69 velos an hour [1]. Both are below the 9.50 minimum wage [1]. [3] Examiner insight: show the working; a correct comparison with a wrong figure still loses the calculation mark.

3. (a) North [1], up 7.4 percentage points (14.2 to 21.6) [1]. (b) The data shows only that unemployment rose over the same period as automation; two things happening together does not prove one caused the other [1]. Other causes in the North, such as other closures or a regional slowdown, are not ruled out [1]. The table gives only 2019 and 2025, so it cannot show whether the rise began after the terminal opened in 2021 [1]. It gives no figures on port jobs lost, so the link to the port is assumed, not shown [1]. [6] Examiner insight: “correlation is not causation” earns credit only when you add what else could explain this particular data.

4. (a) “The port operator predicts 300 new technical jobs by 2028” [1]. (b) “Countries that resist technology always fall behind” (or “Everyone knows robots only make the rich richer”) [1]. It applies a claim to every case with no evidence, so one counter-example would undermine it [1]. [3] Examiner insight: name the generalisation and say what it does to the argument; spotting it alone earns half the marks.

5. Amira values flexibility, as she can “study in the mornings” [1], but wants security, since she “earned nothing” when ill [1]. She holds this view because she carries the risk of illness and low pay herself [1]. App companies warn that fees would rise and riders could lose work [1], so they stress low prices and keeping demand [1]. They hold this view because they compete on cost and have a vested interest in keeping riders self-employed [1]. [6] Examiner insight: marks for “why” need the reason behind each group’s position, not a restatement of what they think.

6. (a) Automation at Kessin port may have cut manual jobs (Source D, terminal opened 2021) [1], which fits the North having the largest rise in Source B [1]. A skills gap: employers say young applicants lack skills (Source C) [1], and the new port jobs are technical, needing training many young people do not have (Sources D and E) [1]. (b) Personal: Amira earns below the minimum wage and nothing when ill [1], so she cannot plan or save [1]. National: the government must spend on schemes such as the 119-million-velo wage subsidy [1], money that cannot go to other services, while unemployed young people pay less tax [1]. [8] Examiner insight: each cause or consequence needs a source reference and one step of development to reach full marks.

7. (a) Only 96 of 1,200 firms replied, an 8% response rate [1]. Firms with complaints may be more likely to reply, so the sample may be biased [1]. The 72.9% is of those who replied, not of all firms [1]. The Forum has a vested interest: it wants the government, not employers, to pay for training [1]. “Basic workplace skills” is not defined, so firms may mean different things [1]. The survey asks about applicants, yet the conclusion blames schools; that link is not tested [1]. It measures employers’ opinions, not how young people actually perform at work [1]. Judgement: weak evidence for the claim about schools, though it may show a perceived problem worth investigating [1]. (b) Survey a random sample of employers of different sizes and regions, not only Forum members [1]. Define workplace skills clearly, such as timekeeping, teamwork and basic IT [1]. Compare supervisors’ ratings of new young staff after six months with ratings of older new staff [1]. Interview young workers and teachers to include other perspectives [1]. Use an independent researcher to remove the vested interest [1]. Check secondary data, such as how many young people complete apprenticeships [1]. [14] Examiner insight: in (b), credit goes to a method that fixes the specific weaknesses you found in (a), not to “do more research”.

8. Indicative content. Marr: uses emotive language (“takes bread from a family’s table”) rather than evidence [1]. His claim that unemployment rose is supported by Source B (14.2% to 21.6%) [1], but “soared” is an exaggeration and he assumes automation caused it [1]. “Everyone knows robots only make the rich richer” is an unsupported generalisation [1]. His proposed ban until “every dock worker has a new job” has no evidence that it would work [1]. Venn: the competition argument is reasoned but gives no evidence about rival ports [1]. 18% more containers shows port success, not more jobs [1]. 640 workers retrained has no total, so we cannot judge the success rate [1]. The 300 jobs is a prediction from the port operator, which has a vested interest [1]. As minister she also has a vested interest in defending her own policy [1]. Comparison: both rely on generalisations, but Venn offers more checkable evidence [1]. Judgement: Venn’s argument is stronger, though neither shows what happened to young people’s jobs [1]. [12] Examiner insight: evaluate the reasoning and evidence in each argument; agreeing or disagreeing with automation itself earns nothing.

9. Indicative content. Criteria: tackles a cause, reaches those most affected, cost and how long it lasts [1]. Action 2: tackles the skills gap identified by employers in Source C [1] and matches the technical jobs the port predicts in Source D [1]. Co-funding by the operator makes it more sustainable than a government-only scheme [1]. It targets the North, where Source B shows the largest rise [1]. But 400 places a year is small and two-year courses are slow [1]. It also relies on the operator’s prediction of 300 jobs, which may not happen [1]. Action 1: could increase hiring quickly [1] and reaches 15,000 young people nationally [1]. But it costs about 119 million velos a year [1], treats the symptom rather than the cause, and jobs may end when the 12 months run out [1]. It is not targeted at the North [1]. Action 3: would improve pay and security for workers like Amira, who earns 7.88 velos an hour [1], but it does not create jobs and may reduce gig work if fees rise [1]. Evidence: much of the evidence comes from groups with vested interests, such as the Forum and the operator, so judgements are provisional [1]. Judgement: Action 2 is most effective because it tackles a cause where the problem is worst; a short targeted subsidy could support young people in the meantime [1]. [16] Examiner insight: high marks need a clear judgement that weighs actions against each other using evidence from several sources.

10. (a) A question with a global scope that people disagree on [1], phrased to allow different perspectives, such as “Should governments pay employers to hire young people?” [1]. (b) National: an employers’ organisation in your country [1], from a report or a national newspaper interview [1]. Global: the International Labour Organization [1], from its published reports on youth employment [1]. [6] Examiner insight: the syllabus asks for clearly different perspectives at different levels; two national views alone will not do.

11. (a) Run an information session with two local employers that offer apprenticeships [1]. Survey students before and after on whether they can name a local apprenticeship [1], with a target such as doubling the number who can [1]. (b) One member surveys students for their perspective [1]. One interviews employers about what they offer and need [1]. One researches a careers adviser’s view and published national data on apprenticeships [1]. [6] Examiner insight: an action with no measure of success limits the planning marks, so say what you will count and when.

Where marks are usually lost

• Using outside knowledge about employment in source-based answers instead of the sources.
• Calling a prediction, such as the 300 new jobs, a fact.
• Writing “biased” without naming the vested interest or quoting the loaded words.
• Treating a percentage from a small, self-selected sample as strong evidence.
• Claiming automation caused unemployment just because both changed over the same period.
• Describing perspectives without explaining why each group holds them.
• Judging actions without criteria, or never reaching a clear judgement.
• Suggesting research methods that do not fix the weaknesses already found.

Next steps

• Check your weak spots with a free diagnostic.
• Revisit the Employment study guide, the Team Project practice and the Individual Report practice.
• Want feedback on your answers? Book a free trial class.

Official syllabus

These questions are based on the Cambridge IGCSE Global Perspectives (0457) syllabus for examination in 2025, 2026 and 2027, Version 2 (published April 2025).