:from 3 different countries
at a British university
in the United States
in different regions of the world
Dynamic Tasks show data in 2 or more time periods and in English grammar time should come at the start or at the end of a sentence .
Here are some examples that use the table above:
The chart below shows the number of international students at a British University over a period of time.
Here are some more examples with dynamic graph example:
The table shows the obesity rate in one country over a period of time.
The table shows average calorie intake in the United States over a period of time.
Click here to see my examples (47 More Words)
The purpose of the overview paragraph is to give a short summary of the main features. Since dynamic graphs feature data over many years , the main overall features are usually changes . These changes include the most notable increases or decreases over a time period.
Importantly, you should describe these changes in words – do not use any numbers or data points from the graph.
So don’t say: “There was a [50%] increase” Say : “The numbers rose [by half] .”
Or, don’t say: “The numbers rose from [1,000 to 2,000]. Say: “The number [doubled]. ”
Or you can simply say [how much] the number increased or decreased by:
| | |
- “Overall, we can see that the number of people taking the bus to work significantly.” – “Overall, we can see that Asian students over the time period.” | - “Overall, we can see that the sales of Japanese cars over the 20-year period.” – “Overall, we can see that employment levels throughout the 3 decades in the graph.” | - , while the number of European students .” – Meanwhile, obesity levels among 18-29 year-olds in the final years of the graph.” |
Let’s see some examples using the same Task 1 graphs from earlier:
Main features :
– Overall, we can see that enrollments by students from Asian countries doubled throughout the time period, while North American students also grew . However, student numbers from Europe and Africa remained relatively consistent over the 2 decades.
– Overall, we can see that the number of Asian students at the university enjoyed steady, significant growth over the 20 years , with North American attendance also increasing in the last 5 years of the graph . Meanwhile, both European and African student numbers remained steady throughout the time period .
Here’s another example:
Take a look at the graphic and complete the task. The table shows the obesity rate in one country over a period of time.
Main features:
– Overall, we can see that every single age group saw an increase in obesity to some extent, with 30-44 year-olds and 45-64 years-olds both increasing continuously and reaching more than double by the end of the time period. Meanwhile, those within the 18-29 and 65-74 age groups also experienced significant rises, though at least their rates seemed to level off from 1999 onwards .
– Overall, we can see that there was a notable increase in obesity among all age groups in the graph. In particular, 18-29 year-olds saw a three-fold rise over the time period , though at least the trend somewhat stabilised after 1999 . Meanwhile, those aged 30-44 and 45-64 experience a more than two-fold increase throughout the time period . Lastly, the eldest age range, the 65-74 year-olds, jumped by a similar amount , but they too levelled off from 1999 onwards .
Next are the Body paragraphs of your Task 1 report. You can write 2 or 3 Body paragraphs.
Body paragraphs describe the main features in detail, including specific numbers from the graph. The data and features in the body paragraph should be similar in some way.
For example, you should describe the increasing categories together in 1 body paragraph. Then write about the decreasing / contrasting categories in a new body paragraph.
I usually use my overview paragraph to guide the structure of my body paragraphs.
Here is the complete example of Task 1 dynamic graphs from before:
Introduction: The line graph illustrates the amount of international students from different continents at a UK university across a 30-year time period .
Overview: Overall, we can see that enrollments by students from Asian countries doubled throughout the time period, while North American students also grew . However, student numbers from Europe and Africa remained relatively consistent over the 2 decades.
Body 1: (increases together)
In regards to the rising number of enrollments, the number of Asian students at the university is the most striking. In 1995, their numbers were 60, before growing consistently to around 90 in 2005 and eventually reaching 120 by 2015. Meanwhile, though the first half of the time period didn’t show an increase among North American students, in 2010 there was a notable jump in their numbers, rising from 40 to around 70 by 2015.
Body 2: (Other / Contrasts together)
Concerning the other two continents however, there were few changes. The amount of African students remained unchanged apart from a slight surge in 2010, rising to around 30, before returning to 20 as it had been in all other years. Likewise, European students fluctuated steadily between approximately 50 and 55 across the entire 20-year time span.
Introduction: The line graph outlines the percentage of obese people in 4 different age groups between 1971 and 2005.
Overview: Overall, we can see that there was a notable increase in obesity among all age groups in the graph. In particular, 18-29 year-olds saw a three-fold rise over the time period , though at least the trend somewhat stabilised after 1999 . Meanwhile, those aged 30-44 and 45-64 experience a more than two-fold increase throughout the time period . Lastly, the eldest age range, the 65-74 year-olds, jumped by a similar amount , but they too levelled off from 1999 onwards .
Body 1: (biggest increase)
Starting with 18-29 year olds, their overall increase in obesity was the most dramatic, despite still being the lowest among all age groups. In 1971, their obesity rate was only around 7 or 8%, but from 1976 there was a sharp increase, rising from 8% to almost 25% by 2001. After this, the rate remained at around 25% from the remainder of the graph.
Body 2: (more increases, but new paragraph because Body 1 is already quite long)
In contrast, not only did 30-44 year-olds and 45-64 years-olds see a huge rise in obesity rates, their numbers continued to climb even after 2001. In the case of the 30-44 age group, their rates doubled from 15 to 30 by 2001, but then climbed once again to 35% by 2005. Likewise, 45-64 year-olds leapt from around 17% to 35% in 2003, before the rate rose even higher to 40% by the end of the graph.
Body 3: (least eventful category – new paragraph because Body 2 is already long)
Finally, the oldest group in the graph, 65-74 year-olds, also saw a steep rise in obesity, but followed a similar pattern to the 18-29 years old in the latter part of the time period. They began at around 17%, and rose to just over 35% by 1999. However, similarly to the youngest group, their rates stabilised at that number and did not increase or decrease in the remaining 6 years.
Introduction : The table reveals the average amount of calories consumed + by Americans + between 1970 and 2010.
Overview : Overall, we can see that the total calorie intake rose, with almost all food groups accounting for a higher calorie total by the end of the 40-year period. The most significant increases were by grains and added fat , while added sugar, fruit, meats, nuts and eggs also contributed, although to a lesser extent. The two exceptions were the dairy and vegetable food groups, whose contributions had dropped by 2010.
Body 1: (Biggest increases)
Beginning with the biggest calorie contributors, grains supplied only 430 calories of an American diet in 1970, which had risen to 575 by 1990 and then to 625 by 2010. Similarly, added fat added the most calories of any other food group with 230 more calories, rising from 410 in 1970 to 640 in 2010.
Body 2: (Slight increases)
Meanwhile, several other food groups made contributions, although smaller. Added sugar constituted 400 calories per person in 1970, compared with 460 in 2010. In the same time period, fruit rose slightly from 70 to 85 calories on average. Lastly, meat, eggs and nuts saw a mere 15 calorie increase from 1970 to 2010.
Body 3: (Decreases)
However, two groups made up slightly less of an average American’s calorie intake than in 1970. Dairy fell from 265 calories in 1970, to 260 in 1990 and then to 255 in 2010. Likewise, the vegetable food group accounts for 5 calories less than in 1970, dropping from 125 to 120 by 2010.
There you go! A high-band approach, several examples and a reliable framework for you to use in your own IELTS Writing test.
Again, if you want to practise more dynamic graph vocabulary and grammar, there are 19 pages of custom-made graphs, exercises and examples to help you improve your writing skills. Click here to learn more !
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The chart below shows how much money is spent in the budget on different sectors by the uae government in 2000..
An IELTS writing task 1 is about writing a report. As it is known that various Types of illustrations are asked in task one. So in this article, a detailed explanation of writing a bar chart essay will be discussed.
A bar chart is a type of illustration in which the data is represented in the form of rectangular horizontal and vertical bars on the X-axis and Y-axis. One variable is shown on the X axis and another one is on Y-axis. The data can be of two or more components over some years or in some quantity etc.
There are particularly three stages in writing a bar chart:-
Planning stage.
Two tasks have to be done in the planning stage. As we know, a report of 150 words is to be written in approximately a time period of 20 minutes and it should not take more than 20 minutes. The planning stage requires at least two to three minutes of planning. One work that has to be done in the planning stage is analyzing the question and the other work is to identify the main features .
For example-
The graph below shows the percentage of part-time workers in each country of the United Kingdom in 1980 and 2010.
Summarise the information by selecting and reporting the main features, and make comparisons where relevant.
So here, in this question, two components are percentages and countries. The data is represented for two years. The green-colored bars are for 1980 and a blue one for 2010.
The percentage is of part-time workers. (Part-time workers can also be written as spare time workers)
1. Wales had the highest count of part-time workers in both years.
2. The proportion of part-time workers in Scotland almost doubled over the time period of 3 decades.
3. The rate of working capital as part-time in the UK increased over the period except for the country of Northern Ireland.
Writing stage.
The writing part is divided into paragraphs which are an introduction, overview, Body paragraphs 1 and 2.
Name of the illustration that is, a bar graph or bar chart
What it shows , is, the percentage of workers
Years that is, 1980 and 2010
The rate of working capital as part-time in the UK increased over the period except for the country of Northern Ireland.
1. Remember that it is not essential to write about each and every bar. You can just write it by mentioning the key features only.
2. Don’t forget to mention the percentages which is an important variable of the graph here.
3. Take care of the years mentioned and write the correct one against the correct country name.
The bar chart shows the percentage of people who have part-time jobs in the countries of the United Kingdom, both in 1980 and in 2010.
Overall, The rate of working capital as part-time in the UK increased over the period except for the country of Northern Ireland.
In 1980, 25% of people in England worked part-time. The only country with a greater percentage of part-time workers was Wales, with around 33% working part-time. Both countries saw an increase in the percentage of people working part-time in 2010. In England, the percentage rose to over 30%, and in Wales, the percentage rose to just over 35%.
Scotland had the smallest percentage of part-time workers in 1980, with just over ten percent. However, this rose to almost 20% in 2010 which is a large increase. Lastly, Northern Ireland was the only country that had a decreasing percentage of part-time workers. In 1980, it had around 15% of people in part-time work. This decreased by a couple of percent in 2010.
Rereading stage.
The proof Reading stage is a very crucial stage and it should take two minutes at least after your writing. In this stage, you have to read and take out the mistakes if any, about what you have written above.
So in the above discussion, it is clear that identification of the key features is very important here. Once you have identified what you have to write, it makes it easier for you to write. The writing of the overview part and the body paragraphs get simpler after this recognition of the important key features. Following are some example questions in which the key features are mentioned for your reference.
The chart shows components of GDP in the UK from 1992 to 2000.
Summarize the information by selecting and reporting the main features and making comparisons where relevant.
The graph gives information about the age of the population of Iceland between 1990 and 2020.
The chart below shows the proportion of male and female students studying six art-related subjects at a UK university in 2011.
The chart below gives the distribution of worldwide car sharing schemes (%) in 2008 and 2016.
Summarise the information by selecting and reporting the main features, and make comparisons where necessary.
Here, for different years, two different Body paragraphs can be formed.
I hope the above article brings the clarity of identification of the key features in detail and it makes you feel confident of writing bar graph in an appropriate manner.
Students can also enroll now in BDS Online IELTS Preparation Course today where you will get access to anytime/anywhere IELTS classes, with 400+ detailed video lectures, sample papers, and live classes by Dr. Roma. Candidates can also sign up for IELTS Dr. Roma Writing Templates + Cue Cards Course to get ready essay templates and solutions latest IELTS essay topics. So let's get started with IELTS writing practice.
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If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.
This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.
Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.
Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.
Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).
Join Lareina Yee and Roger Roberts on Tuesday, July 30, at 12:30 p.m. EDT/6:30 p.m. CET as they discuss the future of these technological trends, the factors that will fuel their growth, and strategies for investing in them through 2024 and beyond.
Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.
Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.
The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.
Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.
As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.
Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).
Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.
In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.
Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.
Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.
The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.
Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.
Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.
To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.
What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.
Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.
In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.
The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.
Alex Singla and Alexander Sukharevsky are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall is an associate partner in the Washington, DC, office.
They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.
This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.
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Vice President Kamala Harris, center, along with Department of Homeland Security Secretary, Alejandro Mayorkas, Rep. Veronica Escobar, a Democrat from Texas, and Sen. Dick Durbin, a Democrat from Illinois, tour a U.S. Customs and Border Protection facility in El Paso, Texas, U.S., in June 2021. Bloomberg/via Getty Images hide caption
As Vice President Kamala Harris works to secure the presidential nomination of the Democratic Party next month, her role on immigration policy is now in the spotlight.
Minutes after the President Joe Biden announced he was dropping out of the race and was endorsing Harris, Republicans started attacking her record on immigration and border policy.
“Joe Biden has now endorsed and fully supports his ‘Borders Czar’ Kamala Harris to be the Democrat candidate for president,” Gov. Greg Abbott, R-Texas, posted on X . “I think I will need to triple the border wall, razor wire barriers and National Guard on the border.”
Conservatives have often referred to Harris as the Biden administration’s "Border Czar," incorrectly claiming she was tasked with repairing the border.
“Kamala had one job,” said Nikki Haley earlier this month at the Republican National Convention. “One job. And that was to fix the border. Now imagine her in charge of the entire country.”
In reality, that was not Harris’ job.
She was tasked by Biden in 2021 to examine the root causes of migration from Central America, including poverty, violence, and corruption. At that time, unauthorized migration came primarily from Mexico and Central America.
She was never tapped to head immigration policy, which is the responsibility of Homeland Security Secretary Alejandro Mayorkas, who oversees all agencies in charge of the enforcement of immigration laws.
Three years later, this role could be Harris’ Achilles' heel. Her role in pushing for Biden’s immigration proposals have disenchanted Democrats and immigrant rights groups.
“I do think there is an opportunity here for Vice President Harris to have a more hopeful message around immigration than even the Biden administration has had in the past,” said Adriel Orozco, a senior policy counsel with the American Immigration Council.
Biden’s policy proposals have included severely restricting most asylum claims at the border and expediting the removal of unauthorized migrants, something immigrant rights groups have opposed.
Suyapa Portillo, a professor of Chicano/a-Latino/a Transnational Studies at Pitzer College, says Harris should try to separate herself from the Biden administration’s “slow move towards immigration reform,” and from the message of deterrence that “represents that conservatism from the Biden administration and the Democratic Party — the old guard.”
Vice President Kamala Harris speaks from the South Lawn of the White House in Washington on Monday during an event with NCAA college athletes. This was her first public appearance since President Joe Biden endorsed her to be the next presidential nominee of the Democratic Party. Susan Walsh/AP hide caption
If Harris secures the presidential nomination, she will be facing a very different immigration landscape than back in 2021, when she was tasked with addressing its root causes.
Last year, unauthorized crossings at the U.S.-Mexico border hit an all-time high. In December 2023, the number of encounters reached nearly 250,000, according to U.S. Customs and Border Protection.
For the last four months, the number of migrants trying to cross illegally has dramatically dropped. That’s due in part due to Mexico’s enforcement, and Biden’s policies, which include severely restricting most asylum claims at the border .
But migration has diversified in the last few years. There is an unprecedented crisis of global displacement. When Harris was elected in 2020, 90% of immigration hailed from Mexico and Central America, according to an analysis by the Migration Policy Institute .
In 2023, only 49 percent of the encounters were with migrants from those four countries.
Today, immigrants arriving at the US Mexico border are fleeing from the crisis in Venezuela, the war in Ukraine and cartel violence in Ecuador, just to name a few.
Harris’ record on immigration has been marred by policy blunders.
Her first international trip as vice president made clear her approach on immigration: addressing root causes to stop illegal migration.
In the summer of 2021, she traveled to Guatemala to meet with then-President Alejandro Giammattei. In a speech, she said that the Biden administration was committed to helping Guatemalans find “hope at home.”
But she also warned prospective migrants.
“I want to be clear to folks in this region who are thinking about making that dangerous trek to the United States-Mexico border,” Harris said. “Do not come. Do not come.”
Those three words: Do not come, were seen by many as a blunder . Latino advocates criticized the statement as paternalistic and tone-deaf, given the violent crises rattling the region.
For many immigrant advocates, that statement continues to haunt Harris’ candidacy.
“She needs to separate from Biden,” Portillo says. “She needs to speak to TPS holders and DACA holders for a plan for legalization, and a border plan that does not include throwing children in jail.”
But Harris has maintained that deterrence is essential: last year she announced $950 million in pledges from private companies to support Central American communities.
Judith Browne Dianis, the executive director of the D.C.-based civil rights organization Advancement Project, says Harris will now have to explain how she would tackle immigration if she were elected president.
“Is it a humanitarian response, or is there a criminalization response?” Dianis says. “We don’t need more criminalization. We don’t need a border wall. We need to get to the root causes. We need to make sure that people are taken care of.”
In early June 2021, Harris came under fire for not visiting the border. In an interview with NBC News , she was asked about Republican critiques.
“And I haven’t been to Europe,” Harris fired back. “I mean, I don’t understand the point that you are making.”
Her response was criticized by conservatives as disconnected and flippant towards border communities and agencies which have felt overwhelmed by the influx of migrants in recent years.
Harris’ first trip to the border came later that month, to El Paso, Texas. At a press conference there, she stated that migration “cannot be reduced to a political issue. We’re talking about children, we’re talking about families, we are talking about suffering.”
Earlier this year, Harris backed a Biden-endorsed bipartisan bill on border enforcement.
The measure would have added immigration detention beds, increased the number of U.S. Customs and Border Protection personnel and asylum officers, and funded technology to detect fentanyl smuggling at the Southern border. It passed in the Senate but failed to move forward after former President Donald Trump urged House Republicans to kill it.
But for many immigration advocates, Harris is their candidate.
Kerri Talbot, the executive director of the national advocacy organization Immigration Hub, called Harris a “strong defender and champion of American families, including their immigrant family members” in a statement Sunday.
“We have no doubt that she can step up to the challenge, counter Trump and JD Vance’s rhetoric and dark vision for democracy, and protect the progress we’ve made while delivering transformative change for our immigration system,” Talbot said.
But Harris involvement with immigration goes way beyond her vice presidency, and her actions show a shift in policies.
When she was the district attorney in San Francisco, she backed a city policy that turned over to federal immigration authorities migrant juveniles suspected of committing a felony. In 2019, Harris’ campaign told CNN “this policy could have been applied more fairly.”
But as California’s attorney general, she had a different stance. In a 2015 interview with CBS Los Angeles, Harris said, “Unfortunately, I know what crime looks like. I know what a criminal looks like who's committing a crime. An undocumented immigrant is not a criminal.”
Harris became U.S. senator from California in 2017.
She was part of a Senate hearing on the Trump administration’s highly controversial separation policy, in which undocumented migrant children were separated from their parents at the U.S.-Mexico border, as a form of immigration deterrence. She questioned Trump officials, and said separating families can cause “irreparable harm.”
In 2019, she and several other Democratic senators reintroduced the Reunite Every Unaccompanied Newborn Infant, Toddler and Other Children Expeditiously (REUNITE) Act , “to expedite the reunification of separated immigrant families and promote humane alternatives for asylum-seeking immigrant families.”
When she ran for president in 2019, Harris unveiled an immigration plan that called for a path to citizenship for recipients of Deferred Action on Childhood Arrivals program, best known as DACA.
That’s similar to what the Biden-Harris campaign promised when they run in 2020. However, none of that has happened during the administration.
There are so many questions written each year, you may find you practice answering various questions on different topics. It is best practice to learn how to answer each one of the various types of writing task 1 questions , from bar charts, line graphs, maps, process etc.
Take a look at the IELTS Writing Task 1 Academic essay example below >>
Overall, marijuana or hashish claimed the top spot from both genders whereas lysergic acid diethylamide (LSD) and recreational use of medical drugs shared the lowest percentage of both male and female students.
Finally, lysergic acid diethylamide and the use of recreational drugs tied at the lowest spot with only 2% from the female students and around 3.5% from the male students.
We hope you found this post useful in helping you to study for the IELTS Test . If you have any questions please let us know in the comments below or on the Facebook page.
Letter to the training organiser to express interest: semi-formal letter [ielts general writing task 1 ], general training writing task 1: semi-formal letter- university, leave a comment cancel reply.
Advertisement
Airlines, hospitals and people’s computers were affected after CrowdStrike, a cybersecurity company, sent out a flawed software update.
By Adam Satariano Paul Mozur Kate Conger and Sheera Frenkel
Airlines grounded flights. Operators of 911 lines could not respond to emergencies. Hospitals canceled surgeries. Retailers closed for the day. And the actions all traced back to a batch of bad computer code.
A flawed software update sent out by a little-known cybersecurity company caused chaos and disruption around the world on Friday. The company, CrowdStrike , based in Austin, Texas, makes software used by multinational corporations, government agencies and scores of other organizations to protect against hackers and online intruders.
But when CrowdStrike sent its update on Thursday to its customers that run Microsoft Windows software, computers began to crash.
The fallout, which was immediate and inescapable, highlighted the brittleness of global technology infrastructure. The world has become reliant on Microsoft and a handful of cybersecurity firms like CrowdStrike. So when a single flawed piece of software is released over the internet, it can almost instantly damage countless companies and organizations that depend on the technology as part of everyday business.
“This is a very, very uncomfortable illustration of the fragility of the world’s core internet infrastructure,” said Ciaran Martin, the former chief executive of Britain’s National Cyber Security Center and a professor at the Blavatnik School of Government at Oxford University.
A cyberattack did not cause the widespread outage, but the effects on Friday showed how devastating the damage can be when a main artery of the global technology system is disrupted. It raised broader questions about CrowdStrike’s testing processes and what repercussions such software firms should face when flaws in their code cause major disruptions.
Here’s a visual explanation for how a faulty software update crippled machines.
Share of canceled flights at 25 airports on Friday
50% of flights
Ai r po r t
Bengalu r u K empeg o wda
Dhaka Shahjalal
Minneapolis-Saint P aul
Stuttga r t
Melbou r ne
Be r lin B r anden b urg
London City
Amsterdam Schiphol
Chicago O'Hare
Raleigh−Durham
B r adl e y
Cha r lotte
Reagan National
Philadelphia
1:20 a.m. ET
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Here is the 5 steps process I recommend for planning and writing IELTS line graph essays: 1) Analyse the question. 2) Identify the main features. 3) Write an introduction. 4) Write an overview. 5) Write the details paragraphs. I'm going to take you through the whole process step-by-step as we work on a practice question.
There are 5 steps to writing a good IELTS bar chart essay: 1) Analyse the question. 2) Identify the main features. 3) Write an introduction. 4) Write an overview. 5) Write the details paragraphs. Use this simple planning process as you practice writing IELTS bar chart essays and you'll have no problem remembering it in the exam.
Introduce the Graph. You need to begin with one or two sentences that state what the IELTS writing task 1 shows. To do this, paraphrase the title of the graph, making sure you put in a time frame if there is one. Here is an example for the above line graph: The line graph compares the fast food consumption of teenagers in Australia between 1975 ...
IELTS Writing Task 1 - Bar Chart Essay Example 1. IELTS Writing Task 1 Academic bar chart essay example that is a band score 8. The question is: The chart below gives information about Someland's main exports in 2005, 2015, and future projections for 2025. Take a look at the sample answer. View high band score examples of IELTS writing task ...
Bonus Tips: How To Write a Line Graph Essay. Transition Words for a Smooth Flow: Transition words like "however," "furthermore," and "in addition" will help connect your ideas and create a logical flow in your essay. Vary Your Sentence Structure: Don't be afraid to mix up short and long sentences to keep your writing engaging.
IELTS Vocabulary. When it comes to IELTS writing task 1, 25% of your marks are for the range of words you use. That means IELTS graph vocabulary is a very important component to review as you prepare for the Writing Task 1. You can start by checking out this IELTS writing task 1 vocabulary guide. And below, I'll provide an overview of words ...
In the first part of IELTS Academic Writing, you can come across different types of graphs: a line or bar graph, a table, a map, a process, two graphs or two tables. You select words and grammatical constructions depending on the type of graph you are writing about. For example, if you got a process (e.g. water cycle on Earth) you use words ...
The process for planning and writing IELTS multiple graph essays is the same as for any other Academic Task 1 essay. Here is the 5 steps process I recommend that you use: 1) Analyse the question. 2) Identify the main features. 3) Write an introduction. 4) Write an overview. 5) Write the details paragraphs.
To make the best use of your time it's important to write with a clear structure, focus on the most important trend or trends, choose appropriate vocabulary and avoid common mistakes. In this tutorial, we have a band range 6.5 / 7 academic task 1 IELTS line graph example essay graded by an ex-IELTS examiner (on our team of essay correctors).
To effectively write about an IELTS Writing Task 1 bar chart, follow these tips. 1. Start by Reading the Title. First and foremost, you should read the title. Often, I have students report on the essay in an inverted order because they didn't read the bar chart title. For example, an IELTS Writing Task 1 bar chart that I give students has the ...
Writing about Charts, Graphs, and Diagrams. Make sure to organize your IELTS Task 1 essay so that the reader can navigate it easily. Step 1: Give a clear overview of what the figure is about, showing that you understand the main message it conveys. Step 2: Describe the data in a systematic way (left to right, top to bottom, biggest to smallest ...
Every graph is a figure but not every figure is a graph. Graphs are a particular set of figures that display quantitative relationships between variables. Some of the most common graphs include bar charts, frequency histograms, pie charts, scatter plots, and line graphs, each of which displays trends or relationships within and among datasets ...
Take a look at the IELTS Writing Task 1 Academic essay example below >>. *This pie chart question and answer were provided by a student. IELTS Achieve did not design this question*. The chart below shows how much money is spent in the budget on different sectors by the UAE government in 2000. Summarize the information by selecting and reporting ...
In writing task 1, you may be asked to write about a chart, line graph, table or proportional bar chart. There is a number of practice questions out there for you to try and perfect your answers in preparation for the Academic IELTS test. In this post, we will be looking at line graphs, bar charts, pie charts, useful vocabulary and describing ...
Providing size context gives your audience a sense of proportion, making the data's impact more meaningful. Examples: "The graph's highest point is $12 million, contrasting sharply with its lowest at $1 million.". "Temperature shifts varied by 40°C, from -20°C in winter to 20°C in summer.".
significant exceptions. anything else that really stands out. There are 3 main features in this graph. 1) It takes over 26 years for a Vietnamese person to buy a car. 2) Vietnam has the second highest average costs but the second lowest wages. 3) Cost of a car in Singapore is nearly 3 times the next most expensive.
2.) Dynamic Graph Overview. The purpose of the overview paragraph is to give a short summary of the main features. Since dynamic graphs feature data over many years, the main overall features are usually changes.These changes include the most notable increases or decreases over a time period.. Importantly, you should describe these changes in words - do not use any numbers or data points ...
Recent IELTS Graph 20: The table below shows the worldwide market share of the notebook computer market for manufacturers in the years 2006, 2007 and 2014. Summarise the information by selecting and reporting the main features and make comparisons where relevant. Answer: The table gives information about the percentages of international market shares of different notebook computer brands in ...
Remember that it is not essential to write about each and every bar. You can just write it by mentioning the key features only. 2. Don't forget to mention the percentages which is an important variable of the graph here. 3. Take care of the years mentioned and write the correct one against the correct country name.
Worksheets and downloads. Writing about a bar chart - exercises 525.21 KB. Writing about a bar chart - answers 170.59 KB. Writing about a bar chart - report 449.01 KB. Writing about a bar chart - writing practice 209.81 KB.
For example, our Similarity Report guidance on help.turnitin is repeated in numerous places to cater for each individual integration and license type. On guides.turnitin this content will exist in a single place to allow for users of all integrations and licenses to find it easily. We have made slight modifications to these guides to help you ...
In this post, we will look at a Writing Task 1 Academic bar chart essay example from the IELTS writing task 1 Academic Test. Students often ask if the questions are repeated year after year and the answer is no, but the type of chart or graph can be. There are so many questions written each year, you may find you practice answering various ...
If 2023 was the year the world discovered generative AI (gen AI), 2024 is the year organizations truly began using—and deriving business value from—this new technology.In the latest McKinsey Global Survey on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago.
This paper characterizes UK public spending pressures over a ten-year horizon and their implications for public deficits and debt levels. The analysis is based on a 'bottom-up' scenario for total public expenditure, that includes, inter alia, implementation of the NHS Long-Term Workforce Plan, public investment to support the Balanced Pathway to Net Zero, and state pension spending under ...
Based on New York Times/Siena College polls of 872 voters in Pennsylvania conducted from July 9 to 11, 2024, and 661 voters in Virginia conducted from July 9 to 12, 2024. By Lily Boyce and Andrew Park
Vice President Harris was tasked to address the roots of mass migration to the U.S. Some of her actions have sparked backlash from across the political spectrum.
Senator J.D. Vance of Ohio, Donald J. Trump's newly chosen running mate, has made a shift from the Trump critic he was when he first entered politics to the loyalist he is today.
IELTS Writing Task 1 - Bar Chart Example Essay 3. In this post, we will look at a Writing Task 1 Academic bar chart essay example from the IELTS writing task 1 Academic Test. Students often ask if the questions are repeated year after year and the answer is no, but the type of chart or graph can be. There are so many questions written each ...
CrowdStrike promised to improve its testing process going forward, according to the report. On Thursday, the tech issues began when Microsoft dealt with an outage on its cloud service system ...
Major Tech Outage Grounds Flights, Hits Banks and Businesses Worldwide CrowdStrike update causes device outages for millions of Microsoft Windows users