The one-sentence truth: “X causes Y” is often where weak GP reasoning begins, because real outcomes usually have mechanisms, conditions, feedback and competing explanations.
General Paper questions constantly invite causal claims. Does technology reduce loneliness? Does inequality undermine trust? Does education improve social mobility? Does censorship increase stability? Does economic growth improve wellbeing? The danger is that students often jump from association to causation because two things appear together.
JC2 vocabulary needs a richer causal map: cause, contributing factor, driver, catalyst, determinant, mechanism, mediator, condition, correlation, confounder, feedback, consequence and unintended effect. These distinctions make essays more realistic and much harder to overstate.
The vocabulary of causation
| Term | Meaning | What it helps you explain |
|---|---|---|
| cause | a factor that helps produce an outcome | What contributes to the result? |
| driver | a factor that pushes a trend or process | What keeps the process moving? |
| determinant | a factor with substantial influence over an outcome | What strongly shapes the result? |
| catalyst | a factor that accelerates or triggers change | What makes change happen faster? |
| mechanism | the process linking cause to effect | How does X produce Y? |
| mediator | an intermediate factor through which an effect occurs | What sits between cause and outcome? |
| condition | a circumstance required for the effect to occur | When does the mechanism operate? |
| correlation | an association between variables | Do they move together without proof of cause? |
| confounder | a third factor that may explain both X and Y | Is another variable creating the appearance of causation? |
| feedback | an effect that loops back to influence its cause | Does the system reinforce or dampen itself? |
1. Cause is not the same as correlation
Two trends can move together without one causing the other. Students should therefore avoid language such as “This proves that X causes Y” unless the mechanism and evidence genuinely support that conclusion.
A better progression is: association, plausible mechanism, corroborating evidence, then causal confidence. If teenage anxiety and social-media use rise together, the relationship may be real, but other factors—sleep, family stress, economic insecurity, selection effects—may also matter.
2. Mechanism: the bridge between cause and effect
A mechanism explains how the cause produces the outcome. “High housing costs reduce fertility” is a claim. “High housing costs may delay household formation by increasing the financial threshold for independent living and child-rearing” identifies a mechanism.
Mechanism vocabulary makes GP paragraphs analytical rather than merely associative.
3. Driver versus determinant
A driver pushes a process. A determinant has stronger explanatory weight. Population ageing may be a major determinant of healthcare demand, while advertising may be one driver of consumption. These words help establish hierarchy among causes.
4. Catalyst: important, but not always fundamental
A catalyst accelerates or triggers change that may already have underlying causes. A political scandal may catalyse reform without being the deeper reason institutions were vulnerable. A technological breakthrough may catalyse adoption while cost, regulation and demand remain the structural drivers.
This distinction is useful when explaining sudden events inside long-running trends.
5. Mediating variables
Sometimes X affects Y through Z. Education may influence health partly through income, information and behaviour. Social media may influence political attitudes through repeated exposure, group identity or recommendation systems.
Using the word mediates helps explain the middle of the chain rather than pretending the cause acts directly.
6. Conditions and contingencies
Many causal relationships operate only under certain conditions. Price increases may reduce consumption where substitutes exist. Regulation may improve safety where enforcement is credible. AI may improve productivity where workflows are redesigned and outputs can be checked.
Useful structures include where, provided that, conditional upon and contingent on.
7. Confounding: the third-factor problem
A confounder can create the appearance that X causes Y when both are influenced by Z. Wealth, for example, can affect both education and health. If we ignore income, we may overstate the direct effect of education on health outcomes.
GP students need not run statistical models. They should simply ask: what other factor could explain both sides of this relationship?
8. Reciprocal causation and feedback
Cause can run both ways. Low trust may weaken institutions, while weak institutions further reduce trust. Economic insecurity can increase political polarisation, while polarisation can make economic reform harder. These are feedback loops.
Recognising reciprocal causation is one of the easiest ways to escape simplistic one-directional essays.
9. Necessary and sufficient causes
A factor may be necessary without being sufficient. Access to technology may be necessary for online learning, but not sufficient if students lack guidance or foundational knowledge. Conversely, some outcomes can arise through several different causal paths, so no single factor is necessary.
10. Proximate and underlying causes
A proximate cause is close to the event. An underlying cause is deeper and more structural. A protest may be triggered by a specific incident, while the underlying causes include inequality, exclusion or institutional distrust.
This vocabulary helps students distinguish spark from fuel.
11. Cause in Paper 2
Writers often imply causation through verbs such as drives, fuels, leads to, results in, contributes to and exacerbates. These verbs carry different strengths. “Contributes to” is weaker than “determines”. “Exacerbates” means worsens an existing problem, not creates it from nothing.
12. Cause in the Application Question
An argument may apply differently to Singapore because the mechanism differs. A policy effect observed overseas may depend on institutions, geography, demographics or social norms that are not identical locally. AQ improves when students ask whether the same causal chain operates in Singapore.
From simple causation to JC2 reasoning
Weak: “Social media causes polarisation.”
Better: “Social media can contribute to polarisation.”
Stronger: “Social-media platforms can intensify polarisation where recommendation systems reward emotionally provocative content and users self-select into like-minded networks; however, pre-existing political divisions may also drive the same online behaviour.”
The final version contains mechanism, condition, reciprocal causation and an alternative explanation.
A seven-day causation drill
- Day 1: replace five “X causes Y” claims with more precise causal verbs.
- Day 2: identify the mechanism linking cause and effect.
- Day 3: separate drivers from determinants.
- Day 4: find one plausible confounder for five correlations.
- Day 5: identify reciprocal causation or feedback in two social issues.
- Day 6: paraphrase causal verbs without changing their strength.
- Day 7: write one timed paragraph with cause, mechanism, condition and alternative explanation.
JC2 causation health check
- Can you distinguish correlation from causation?
- Can you name the mechanism?
- Can you distinguish catalyst, driver and determinant?
- Can you identify a confounder?
- Can you recognise feedback or reciprocal causation?
- Can you explain when the causal relationship stops holding?
Continue the JC2 GP vocabulary system
Return to the canonical General Paper Vocabulary Year 2 (JC2): Top 100 Words for A-Level GP 8881 for the full vocabulary map.
For the broader JC progression into adult thinking and professional writing, read Vocabulary for Junior College (JC1–JC2): Adult Thinking, Professional Writing.
Final thought
The strongest causal sentence is rarely the most certain one. It is the one that shows the mechanism, names the conditions, considers alternatives and tells the reader exactly how much causal weight the evidence can carry.
Phase 4 Mastery Lab: causal reasoning as a map
A strong JC2 causal paragraph should be drawable. Start with X → mechanism → intermediate change → outcome, then add the conditions that strengthen or weaken each arrow. This prevents the common mistake of jumping from a topic to an outcome with no explanation in between.
Worked example: housing costs and family formation
“Housing costs reduce fertility” is too compressed. One plausible chain is: higher housing costs raise the financial threshold for independent household formation; delayed household formation can postpone partnership or childbearing decisions; uncertainty about future affordability can reinforce that delay. But income growth, childcare costs, work expectations, cultural preferences and housing policy may mediate or confound the relationship. The causal claim becomes more credible because the middle of the chain is visible.
Worked example: recommendation algorithms and polarisation
A platform may amplify polarisation if engagement systems repeatedly expose users to emotionally provocative content and if users preferentially interact with like-minded communities. Yet selection effects matter: already polarised users may seek more partisan material. Feedback can then run both ways. The platform changes exposure, while user behaviour changes what the platform learns to recommend.
Causal verbs by strength
| Expression | Typical commitment |
|---|---|
| is associated with | Relationship observed; causation not established. |
| contributes to | One causal factor among several. |
| enables / facilitates | Makes an outcome easier or possible without determining it. |
| drives | Provides substantial causal force. |
| precipitates | Triggers or brings about a relatively immediate change. |
| determines | Very strong causal language; use only where alternatives are tightly constrained. |
Paper 1 causal paragraph builder
- Claim: identify the effect without overstating it.
- Mechanism: explain the process linking cause to outcome.
- Condition: state where the mechanism is strongest.
- Alternative: identify another plausible explanation or contributing factor.
- Evaluation: decide how much causal weight X really deserves.
Paper 2 causal preservation
When paraphrasing, preserve both direction and strength. “A may contribute to B” cannot become “B is caused by A”. “X exacerbates Y” means Y already exists and becomes worse. “X enables Y” means X makes Y possible, not that Y must occur. These distinctions are part of the author’s argument.
AQ transfer: does the same mechanism exist in Singapore?
Do not transfer an overseas causal conclusion simply because the topic is familiar. Ask whether the same incentives, institutions, population structure and constraints operate locally. A claim about car dependence, for example, may weaken where public transport provides a credible substitute; a claim about information access may change where digital connectivity is high but language, confidence or verification skills vary.
Causal self-marking rubric
- Weak: X causes Y, followed by an example.
- Developing: uses a more careful causal verb but no mechanism.
- Competent: identifies mechanism and condition.
- Strong: considers confounders, mediation or feedback.
- Excellent: ranks causal weight and explains what evidence would change the conclusion.
The goal is not to make causation sound complicated. It is to make the causal story explicit enough that a reader can test it.