Foram encontradas 130 questões.
Disciplina: Administração Financeira e Orçamentária
Banca: FGV
Orgão: Câm. Deputados
O ciclo orçamentário abrange as seguintes etapas: elaboração da proposta, apreciação legislativa, execução, controle e avaliação. Refere-se ao intervalo de tempo durante o qual ocorrem as atividades características do orçamento público, desde sua concepção até a avaliação final.
Acerca do ciclo orçamentário, avalie as afirmativas a seguir e assinale (V) para a verdadeira e (F) para a falsa.
( ) A elaboração da proposta orçamentária envolve a consolidação pelo Poder Legislativo do projeto da lei orçamentária anual, abrangendo as propostas orçamentárias dos demais Poderes, seguida do envio ao Poder Executivo para apreciação.
( ) A execução orçamentária compreende a utilização dos créditos consignados no Orçamento Geral da União, visando à realização das ações atribuídas às unidades orçamentárias. Envolve os três estágios da receita: empenho, liquidação e pagamento.
( ) A avaliação orçamentária consiste na avaliação do cumprimento das metas previstas na LOA e da execução dos programas de governo e dos orçamentos da União, abrangendo também a avaliação dos resultados, quanto à eficácia e eficiência, da gestão orçamentária, financeira e patrimonial nos órgãos e entidades da administração federal, bem como da aplicação de recursos públicos por entidades de direito privado.
As afirmativas são, respectivamente,
Provas
Disciplina: Administração Financeira e Orçamentária
Banca: FGV
Orgão: Câm. Deputados
Na análise das matérias orçamentárias, os membros das casas Legislativas desempenham uma gama de atividades que incluem estudos, avaliações, debates e consultas, bem como a busca de informações e a participação em audiências públicas com autoridades e especialistas.
A Constituição Federal de 1988 restaurou o poder do legislador de emendar o projeto de Lei Orçamentária Anual (LOA), especialmente no que se refere ao aumento ou à criação de novas despesas.
As emendas ao projeto de LOA ou aos projetos que o modifiquem podem ser aprovadas caso
Provas
Disciplina: Administração Financeira e Orçamentária
Banca: FGV
Orgão: Câm. Deputados
Os Princípios Orçamentários têm como objetivo estabelecer diretrizes fundamentais que buscam conferir racionalidade, eficiência e transparência aos procedimentos relacionados à criação, implementação e fiscalização do orçamento público.
Em relação aos Princípios Orçamentários aplicáveis aos Poderes Executivo, Legislativo e Judiciário em todas as esferas governamentais, assinale a opção correta.
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
“as yet” in “there is as yet little evidence” (4th paragraph) can be replaced without significant change of meaning by
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
In the last sentence of the first paragraph, when the paper mentions an “upheaval”, it refers to the possibility of a future
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
By calling some economists “doom-mongers” in “Few of the doom-mongers have a good explanation” (2nd paragraph), the authors
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
If someone ends up “on the economic scrapheap” (1st paragraph), this person will feel
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
The adjective in “astonishing breakthroughs” (1st paragraph) is similar in meaning to
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
The title of the article means to
Provas
Read Text II and answer the seven questions that follow it
Text II
Boy cries Wolf
After astonishing breakthroughs in artificial intelligence, many people worry that they will end up on the economic scrapheap. Global Google searches for “is my job safe?” have doubled in recent months, as people fear that they will be replaced with large language models (LLMS). Some evidence suggests that widespread disruption is coming. In a recent paper Tyna Eloundou of OpenAI and colleagues say that “around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of LLMS”. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.
Economists, however, tend to enjoy making predictions about automation more than they enjoy testing them. In the early 2010s many of them loudly predicted that robots would kill jobs by the millions, only to fall silent when employment rates across the rich world rose to all-time highs. Few of the doom-mongers have a good explanation for why countries with the highest rates of tech usage around the globe, such as Japan, Singapore and South Korea, consistently have among the lowest rates of unemployment.
Here we introduce our first attempt at tracking AI’s impact on jobs. Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative AI, which is becoming ever better at logical reasoning and creativity.
However, there is as yet little evidence of an AI hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative AI has risen by half a percentage point.
It is, of course, early days. Few firms yet use generative-AI tools at scale, so the impact on jobs could merely be delayed. Another possibility, however, is that these new technologies will end up destroying only a small number of roles. While AI may be efficient at some tasks, it may be less good at others, such as management and working out what others need.
AI could even have a positive effect on jobs. If workers using it become more efficient, profits at their company could rise which would then allow bosses to ramp up hiring. A recent survey by Experis, an IT-recruitment firm, points to this possibility. More than half of Britain’s employers expect AI technologies to have a positive impact on their headcount over the next two years, it finds.
To see how it all shakes out, we will publish updates to this analysis every few months. But for now, a jobs apocalypse seems a way off.
From The Economist June 17th 2023, p. 71
Based on Text II, mark the statements below as TRUE (T) or FALSE (F).
( ) Many believe AI will eventually make jobs redundant.
( ) The conclusion of the text is that the current outlook regarding employment is rather bleak.
( ) The authors prefer to probe forthcoming evidence before issuing unequivocal accounts.
The statements are, respectively,
Provas
Caderno Container