Unit 4 - Essays - DTM SIMPLE ENGLISH UPDATED Flashcards
“How Useful is the Demographic Transition Model (DTM) for Predicting Population Growth in LICs/MICs?”
Paragraph 1: Cultural and Political Differences Can Make the DTM Wrong
Point 1: The DTM is based on Western countries, but cultures are different around the world.
The DTM says that birth rates fall when countries develop, but this is not always true.
Some cultures, especially in Sub-Saharan Africa, believe that having large families is important.
Example: Niger has a birth rate of 44 births per 1,000 people in 2020, even though it is developing.
This shows that the DTM does not always work because culture can keep birth rates high, even when a country is developing.
Point 2: Governments can change birth rates, which the DTM does not predict.
Some governments try to increase birth rates, while others try to decrease them.
Example 1: Nigeria has encouraged families to have more children, going against what the DTM predicts.
Example 2: India tried to reduce birth rates in the 1970s through forced sterilization policies.
Evaluation: Since government policies can change population trends quickly, the DTM does not always predict what will happen in a country.
Paragraph 2: The DTM Does Not Work Well Because LICs Start with Very High Birth Rates
Point 1: LICs today have much higher birth rates than Western countries did in the past.
The DTM assumes that all countries follow the same pattern, but some LICs start with much higher birth rates than Western countries ever did.
Example: Niger (44 births per 1,000 people in 2020) vs. Europe in the 1800s (about 35 births per 1,000 people).
This means that it takes longer for these countries to lower their birth rates, and the DTM does not predict this well.
Point 2: Death rates are falling faster than the DTM predicts.
The DTM assumes that death rates will slowly decrease, but in many LICs, modern medicine has caused them to drop very quickly.
Example: Bangladesh – Child mortality fell from 87 per 1,000 in 2000 to 34 per 1,000 in 2020 due to vaccines and better hospitals.
Evaluation: The DTM assumes a slow decline, but in reality, many LICs see rapid improvements, making the model less accurate.
Paragraph 3: The DTM is Still Useful for Some Things
Point 1: The DTM correctly predicts that birth rates fall when countries develop.
Even though the DTM is not always correct, it does predict that birth rates go down when countries become wealthier.
Example: Kenya’s birth rate fell from 45 per 1,000 in 1980 to 28 per 1,000 in 2020 because more women are educated, and family planning is more common.
This shows that the DTM can still be useful, even if it does not apply perfectly to every country.
Point 2: The DTM correctly predicts that cities have lower birth rates than rural areas.
In cities, families usually have fewer children because it is expensive, and people have better access to contraceptives.
Example: India – Urban birth rates are much lower than rural birth rates.
Evaluation: The DTM is still useful in explaining why urban areas move through the model faster than rural areas.
Paragraph 4: The World is Changing Faster Than the DTM Predicts
Point 1: Changes are happening much faster today than in the past.
The DTM is based on how Western countries developed over hundreds of years, but many LICs/MICs are now changing in just a few decades.
Example: South Africa – AIDS-related deaths dropped by 60% between 2004 and 2020 because of new treatments.
This rapid change does not fit well with the DTM, which assumes that these shifts happen very slowly.
Point 2: Better access to birth control is changing populations quickly.
The DTM was based on a time when birth control was not common, but today, many LICs and MICs have easy access to contraception.
Example: Southeast Asia – Use of birth control increased from 38% in 1990 to 61% in 2020, leading to lower birth rates.
Evaluation: Because modern technology and medicine are changing populations so quickly, the DTM struggles to predict what will happen.
Conclusion
The DTM is useful for explaining some population changes, like how birth rates fall in urban areas and wealthier countries.
However, it has many problems, such as not considering culture, government policies, and rapid medical advances.
Final judgement: The DTM is a good basic model, but it needs to be updated and adjusted to work better for modern LICs and MICs.
