Latin = and others
For a complete list of Common Scholarly Abbreviations, please see Section 7.4 in the 6th edition of the MLA Handbook for Writers of Research Papers .
Note: When documenting sources using MLA style, the normal punctuation is omitted for degrees when used in parentheses, tables, works cited, footnotes, endnotes, etc. For example, B.A. is written as BA. Other abbreviations retain the periods if applicable, e.g. acad., bib., misc. Italics = Latin
) | ) |
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Also, g reat post to read about US and Canada Map .
Acronym Finder . Look up acronyms, abbreviations and their meanings.
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Common Abbreviations for posting messages on Bulletin Boards – from BabyCentre.co.uk. Examples: AKA = Also known as, LOL = Laughing out loud, BTW = By the way, CUL = See you later, Yw/Ty = You’re welcome/thank you. Emotions: 🙂 or 🙂 = Smiling (Happy), 🙁 or 🙁 = Frowning (Sad), 😮 = Shouting, xxooxxoo = Love (or hugs) & kisses. See also Shorthand and Meaning from Genealogy.com. (Scroll way down the page to view Shorthand). Examples: = I’m grinning, IMHO = in my humble opinion, FYI = for your information, FWIW = for what it’s worth, ROTFL = rolling on the floor laughing, WTG = way to go, Emotions: 😉 or 😉 = winking, 😀 or 😀 = laughing.
Common Abbreviations from Fact Monster for kids.
Common Abbreviations, Common Symbols, Acronyms for Organizations from Web-based Training Modules funded by the U.S. National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER) Program.
Common Abbreviations from U.S. Department of State.
Common Abbreviations and Acronynms from AllEarsNet.com – Deb’s Unofficial Walt Disney World Information Guide.
Common Abbreviations in Writing.
Common Abbreviations Used in International Narcotics Control Strategy Report.
HyperWar – World War II on the WorldWideWeb – Abbreviations, Acronyms, Codewords, Terms .
Military Abbreviations and Acronyms of the US Armed Forces.
Also, great post to read concerning Abbreviations for Books of the Bible .
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Published on 23 May 2022 by Tegan George . Revised on 25 October 2022.
A list of abbreviations is an alphabetical list of abbreviations that you can add to your thesis or dissertation. If you choose to include it, it should appear at the beginning of your document, just after your table of contents .
Abbreviation lists improve readability, minimising confusion about abbreviations unfamiliar to your reader. This can be a worthwhile addition to your thesis or dissertation if you find that you’ve used a lot of abbreviations in your paper.
If you only use a few abbreviations, you don’t necessarily need to include a list. However, it’s never a bad idea to add one if your abbreviations are numerous, or if you think they will not be known to your audience.
You can download our template below in the format of your choice to help you get started.
Download Word doc Download Google doc
Be assured that you'll submit flawless writing. Upload your document to correct all your mistakes.
Best practices for abbreviations and acronyms, additional lists to include, frequently asked questions.
There are a few rules to keep in mind about using abbreviations in academic writing. Here are a few tips.
As well as the list of abbreviations, you can also use a list of tables and figures and a glossary for your thesis or dissertation.
Include your lists in the following order:
As a rule of thumb, write the explanation in full the first time you use an acronym or abbreviation. You can then proceed with the shortened version. However, if the abbreviation is very common (like UK or PC), then you can just use the abbreviated version straight away.
Be sure to add each abbreviation in your list of abbreviations !
If you only used a few abbreviations in your thesis or dissertation, you don’t necessarily need to include a list of abbreviations .
If your abbreviations are numerous, or if you think they won’t be known to your audience, it’s never a bad idea to add one. They can also improve readability, minimising confusion about abbreviations unfamiliar to your reader.
A list of abbreviations is a list of all the abbreviations you used in your thesis or dissertation. It should appear at the beginning of your document, immediately after your table of contents . It should always be in alphabetical order.
An abbreviation is a shortened version of an existing word, such as Dr for Doctor. In contrast, an acronym uses the first letter of each word to create a wholly new word, such as UNESCO (an acronym for the United Nations Educational, Scientific and Cultural Organization).
Your dissertation sometimes contains a list of abbreviations .
If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.
George, T. (2022, October 25). List of Abbreviations | Example, Template & Best Practices. Scribbr. Retrieved 27 July 2024, from https://www.scribbr.co.uk/thesis-dissertation/abbreviations-list/
Other students also liked, dissertation table of contents in word | instructions & examples, dissertation title page, research paper appendix | example & templates.
Table of Contents
Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.
Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.
This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.
A research proposal¹ ,² can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.
With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.
A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.
Research proposals can be written for several reasons:³
Research proposals should aim to answer the three basic questions—what, why, and how.
The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.
The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.
The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.
Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.
If you want to know how to make a research proposal impactful, include the following components:¹
1. Introduction
This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.
2. Literature review
This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.
3. Objectives
Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.
4. Research design and methodology
Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.
5. Ethical considerations
This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.
6. Budget/funding
Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.
7. Appendices
This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.
8. Citations
Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5
Key Takeaways
Here’s a summary of the main points about research proposals discussed in the previous sections:
Q1. How is a research proposal evaluated?
A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6
Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?
A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.
Q3. How long should a research proposal be?
A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.
Arts programs | 1,000-1,500 | |
University of Birmingham | Law School programs | 2,500 |
PhD | 2,500 | |
2,000 | ||
Research degrees | 2,000-3,500 |
Q4. What are the common mistakes to avoid in a research proposal ?
A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7
Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.
This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.
References
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Our only agenda is to publish the truth so you can be an informed participant in democracy. We need your help.
Vice President Kamala Harris waves as she boards Air Force Two after a campaign event July 23, 2024, in Milwaukee. (AP)
If your time is short.
In March 2021, President Joe Biden tasked Vice President Kamala Harris with working alongside officials in Guatemala, El Salvador and Honduras to address the issues driving people to leave those countries and come to the United States.
The Biden-Harris administration said it would focus on five key issues: economic insecurity, corruption, human rights, criminal gang violence and gender-based violence.
Border security and management is the Homeland Security secretary’s responsibility.
Vice President Kamala Harris might soon get a new official title: 2024 Democratic presidential nominee. In the meantime, Republicans have revived a title they gave her in 2021: "border czar."
Claims that President Joe Biden named Harris the "border czar" and that she is responsible for overseeing U.S. border enforcement gained prominence at the Republican National Convention as the party sought to link her to his immigration policy.
The refrain intensified once Biden dropped out of the race and endorsed Harris. It was echoed in ads and by Trump campaign surrogates, including Ohio Sen. J.D. Vance , the Republican vice presidential nominee.
"Here’s Biden appointing Kamala Harris to be his border czar to deal with illegal immigration," a narrator says in a video the Republican National Committee posted on its X account, @GOP. "And here are a record number of illegal immigrants — 10 million and counting — flooding over the border after Harris was put in charge of stopping illegal immigration."
We’ve repeatedly fact-checked claims about the number of people entering the U.S. illegally under Biden. The federal data tracks how many times officials encountered a person trying to cross the southern border, but it doesn’t reflect the number of people let in. And if one person tries to cross the border multiple times, that counts as multiple encounters, even if it’s the same person.
For this fact-check, we’re focused on the scope of Harris’ border responsibilities.
"Border Czar Kamala Harris' reversal of President Trump's immigration policies has created an unprecedented and illegal immigration, humanitarian and national security crisis on our southern border," Trump campaign National Press Secretary Karoline Leavitt told PolitiFact in a statement.
But Biden didn’t put Harris in charge of overseeing border security.
In a meeting with Harris in March 2021 , Biden said Harris would lead U.S. diplomatic efforts and work with officials in Mexico, Guatemala, El Salvador and Honduras to stem migration to the U.S. Biden said that when he was vice president, he "got a similar assignment" and that the Obama administration secured $700 million to help countries in Central America.
"One of the ways we learned is that if you deal with the problems in country, it benefits everyone. It benefits us, it benefits the people, and it grows the economies there," Biden said then.
Biden asked Harris "to be the chief diplomatic officer with Central American countries" and address the root causes that make people leave their home countries, said Michelle Mittelstadt, communications director for the Migration Policy Institute, a nonpartisan think tank.
Managing the border "has always been" the Homeland Security secretary’s role, Mittelstadt said.
Biden tasked Harris with addressing the root causes influencing people’s decisions to migrate to the United States.
"I’ve asked her … to lead our efforts with Mexico and the Northern Triangle and the countries that help — are going to need help in stemming the movement of so many folks, stemming the migration to our southern border," Biden said in March 2021.
Biden held a similar role as vice president to former President Barack Obama. In a 2015 New York Times opinion piece, Biden said he would work with the Northern Triangle’s leaders on security, anti-corruption and investment efforts in the region.
"Donald Trump’s administration didn’t really sustain this strategy, but what Harris sought to revive in 2021 ran along the same lines," said Adam Isacson, defense oversight director at Washington Office on Latin America, a group advocating for human rights in the Americas.
Within weeks of Biden’s remarks about Harris’ role, Republicans including Texas Gov. Greg Abbott and Rep. Steve Scalise, R-La., began calling Harris the " border czar " often in tandem with pointing out she had not yet been to the border.
In April 2021, when a reporter asked Harris whether she would visit the border, she said that her role is addressing the factors that make people leave their home countries, not managing the border.
"The president has asked (Homeland Security) Secretary (Alejandro) Mayorkas to address what is going on at the border. And he has been working very hard at that, and it’s showing some progress because of his hard work," Harris said at an event . "I have been asked to lead the issue of dealing with root causes in the Northern Triangle, similar to what the then-vice president did many years ago."
Harris said she’d focus on economic struggles, violence, corruption and food insecurity in the countries.
In June 2021, Harris visited El Paso, Texas, with Mayorkas. They outlined their responsibilities to reporters. Harris said she was addressing "the root causes of migration, predominantly out of Central America," and Mayorkas said, "It is my responsibility as the Secretary of Homeland Security to address the security and management of our border."
But this distinction didn’t stop critics from linking Harris with U.S.-Mexico border security.
"The administration’s messaging on this in mid-2021 was not as clear as it should have been," Isacson said. "But at no time did Harris or the White House state that her duties included the U.S.-Mexico border, or border security."
Immigration experts said it’s hard to measure Harris’ success in her role, and that a "root causes" approach implies that the results will be seen long term, not immediately.
In July 2021, the administration published a strategy , with Harris writing the lead message, for confronting the factors that drive migration in Central America. The plan focused on economic insecurity, corruption, human rights, criminal gang violence and gender-based violence.
In March 2024, the administration said it secured more than $5.2 billion in private sector investments to the region. However, only about $1 billion has been distributed, the Partnership for Central America, a group working with the administration, reported .
The White House said the investments have generated more than 70,000 new jobs in Guatemala, Honduras and El Salvador, provided job training to 1 million people and expanded digital access to 4.5 million people.
"Still, her engagement on this issue has been sporadic," Isacson said. "She has not traveled very often to the region or otherwise sought to make ‘root causes in Central America’ a central theme of her vice presidency."
Illegal immigration at the U.S. southern border from Guatemala, Honduras and El Salvador has dropped since 2021. Encounters with people from other countries, Venezuela, have risen .
"But it’s hard to prove that U.S. assistance is a central reason" for the Northern Triangle countries’ decline, Isacson said.
The issues pushing people to leave Central American countries "are extremely complex and require deep restructuring of so much in those societies," said Cecilia Menjivar, a sociology professor at the University of California, Los Angeles who specializes on immigration. "So it’s very difficult for one person to change all that, even if it is a powerful person."
Immigration patterns at the U.S.-Mexico border have more to do with conditions in Latin American countries than "any U.S. policy," Mittelstadt said.
For example, a humanitarian crisis in Venezuela has displaced nearly 8 million people since 2014, according to the United Nations. Political, economic and security crises in Cuba, Nicaragua, Haiti and Ecuador have also led to more migration from these countries, Mittelstadt said.
In contrast, immigration encounters with people from El Salvador have dropped in past years, partly because of the country’s crime crackdown .
The Republican National Committee said Biden appointed Harris "to be his border czar to deal with illegal immigration...Harris was put in charge of stopping illegal immigration."
Biden tasked Harris with addressing the root causes that drive migration to the United States. He did not task her with controlling who and how many people enter the southern U.S. border. That's the Homeland Security secretary’s responsibility.
Experts say that seeing the results of addressing root causes driving people out of Guatemala, El Salvador and Honduras — violence, economic insecurity and corruption — takes time.
The statement contains an element of truth, but it ignores critical facts that would give a different impression. We rate it Mostly False.
The Principles of the Truth-O-Meter
Truth Social, post , July 22, 2024
The Hill, House Republicans tee up vote condemning Harris as ‘border czar’ , July 23, 2024
C-SPAN, Sen. J.D. Vance campaign rally in Radford, Virginia , July 22, 2024
GOP, post on X , July 21, 2024
PolitiFact, Francis Suarez’s misleading claim about millions of migrants getting free cellphones, plane tickets , July 28, 2024
PolitiFact, There aren’t 20 million to 30 million immigrants in the U.S. illegally, as Sen. Marco Rubio claimed , June 11, 2024
The White House, Remarks by President Biden and Vice President Harris in a meeting on immigration , March 24, 2021
PolitiFact, Central America and the root causes of migration to the US , June 7, 2021
The New York Times, Joe Biden: A Plan for Central America , Jan. 29, 2015
The White House, Remarks by Vice President Harris at virtual roundtable of experts on the Northern Triangle , April 14, 2021
The White House, Remarks by Vice President Harris, Secretary of Homeland Security Mayorkas, Chairman Durbin, and Representative Escobar in press gaggle , June 25, 2021
Fox News, Obama-era DHS secretary: 'There's a real problem' when you have 'bipartisan outrage' , July 23, 2024
The White House, FACT SHEET: Strategy to address the root causes of migration in Central America , July 29, 2021
The White House, FACT SHEET: Vice President Harris announces public-private partnership has generated more than $5.2 billion in private sector commitments for Northern Central America , March 25, 2024
Migration Policy Institute, Shifting patterns and policies reshape migration to U.S.-Mexico border in major ways in 2023 , October 2023
United Nations High Commissioner for Refugees, Venezuela crisis explained , April 17, 2024
PolitiFact, Donald Trump fact-check: 2024 RNC speech in Milwaukee full of falsehoods about immigrants, economy , July 19, 2024
CBS News, The facts about Kamala Harris' role on immigration in the Biden administration , July 23, 2024
Email interview, Michelle Mittelstadt, communications director for the Migration Policy Institute, July 22, 2024
Email interview, Adam Isacson, defense oversight director at Washington Office on Latin America, July 22, 2024
Email interview, Henry Ziemer, research associate for the Center for Strategic and International Studies, July 22, 2024
Email interview, Cecilia Menjivar, sociology professor at the University of California, Los Angeles, July 22, 2024
Statement, Karoline Leavitt, Trump campaign national press secretary, July 23, 2024
More by maria ramirez uribe.
A new research paper has examined all 29,078 US stocks that have existed since 1926 and identified the top 10 performers of all time.
These stocks, some of them household names, have generated enormous wealth for those who purchased even just one share of the company and held on to it for nearly 100 years.
Of course, identifying the 10 best-performing stocks for the next 100 years is nearly impossible, as the paper's author points out.
"The majority (51.6%) of these stocks had negative cumulative returns," finance professor Hendrik Bessembinder of Arizona State University wrote.
But with a healthy dose of luck, $1 invested in 1926 would have been worth $2.67 million at the end of 2023, assuming it was invested in the right company.
Bessembinder also observed that the 10 best-performing stocks delivered consistently modest annualized gains, reinforcing the slow and steady mantra championed by long-term investors.
"Annualized compound returns to these top performers relatively were modest, averaging 13.47% across the top seventeen stocks, thereby affirming the importance of 'time in the market," Bessembinder wrote.
From soda to cigarettes to computers and airplanes, these are the 10 top-performing US stocks since 1926, according to the paper, which assumed that dividends were reinvested.
Ticker: PEP Return of $1 invested : $86,360 Investment date: December 31, 1925 - December 29, 2023
Ticker: KO Return of $1 invested : $123,724 Investment date: December 31, 1925 - December 29, 2023
Ticker: SPGI Return of $1 invested : $128,787 Investment date: February 14, 1929 - December 29, 2023
Ticker: ETN Return of $1 invested : $151,173 Investment date: December 31, 1925 - December 29, 2023
Ticker: IBM Return of $1 invested : $175,437 Investment date: December 31, 1925- December 29, 2023 5. Boeing
Ticker: BA Return of $1 invested : $212,206 Investment date: September 5, 1934 - December 29, 2023
Ticker: GD Return of $1 invested : $220,850 Investment date: January 28, 1926 - December 29, 2023
Ticker: Delisted after 2021 acquisition by Canadian Pacific Return of $1 invested : $361,757 Investment date: December 31, 1925 - December 13, 2021
Ticker: VMC Return of $1 invested : $393,492 Investment date: December 31, 1925- December 29, 2023
Ticker: MO Return of $1 invested : $2,655,290 Investment date: December 31, 1925 - December 29, 2023
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One thing that makes large language models (LLMs) so powerful is the diversity of tasks to which they can be applied. The same machine-learning model that can help a graduate student draft an email could also aid a clinician in diagnosing cancer.
However, the wide applicability of these models also makes them challenging to evaluate in a systematic way. It would be impossible to create a benchmark dataset to test a model on every type of question it can be asked.
In a new paper , MIT researchers took a different approach. They argue that, because humans decide when to deploy large language models, evaluating a model requires an understanding of how people form beliefs about its capabilities.
For example, the graduate student must decide whether the model could be helpful in drafting a particular email, and the clinician must determine which cases would be best to consult the model on.
Building off this idea, the researchers created a framework to evaluate an LLM based on its alignment with a human’s beliefs about how it will perform on a certain task.
They introduce a human generalization function — a model of how people update their beliefs about an LLM’s capabilities after interacting with it. Then, they evaluate how aligned LLMs are with this human generalization function.
Their results indicate that when models are misaligned with the human generalization function, a user could be overconfident or underconfident about where to deploy it, which might cause the model to fail unexpectedly. Furthermore, due to this misalignment, more capable models tend to perform worse than smaller models in high-stakes situations.
“These tools are exciting because they are general-purpose, but because they are general-purpose, they will be collaborating with people, so we have to take the human in the loop into account,” says study co-author Ashesh Rambachan, assistant professor of economics and a principal investigator in the Laboratory for Information and Decision Systems (LIDS).
Rambachan is joined on the paper by lead author Keyon Vafa, a postdoc at Harvard University; and Sendhil Mullainathan, an MIT professor in the departments of Electrical Engineering and Computer Science and of Economics, and a member of LIDS. The research will be presented at the International Conference on Machine Learning.
Human generalization
As we interact with other people, we form beliefs about what we think they do and do not know. For instance, if your friend is finicky about correcting people’s grammar, you might generalize and think they would also excel at sentence construction, even though you’ve never asked them questions about sentence construction.
“Language models often seem so human. We wanted to illustrate that this force of human generalization is also present in how people form beliefs about language models,” Rambachan says.
As a starting point, the researchers formally defined the human generalization function, which involves asking questions, observing how a person or LLM responds, and then making inferences about how that person or model would respond to related questions.
If someone sees that an LLM can correctly answer questions about matrix inversion, they might also assume it can ace questions about simple arithmetic. A model that is misaligned with this function — one that doesn’t perform well on questions a human expects it to answer correctly — could fail when deployed.
With that formal definition in hand, the researchers designed a survey to measure how people generalize when they interact with LLMs and other people.
They showed survey participants questions that a person or LLM got right or wrong and then asked if they thought that person or LLM would answer a related question correctly. Through the survey, they generated a dataset of nearly 19,000 examples of how humans generalize about LLM performance across 79 diverse tasks.
Measuring misalignment
They found that participants did quite well when asked whether a human who got one question right would answer a related question right, but they were much worse at generalizing about the performance of LLMs.
“Human generalization gets applied to language models, but that breaks down because these language models don’t actually show patterns of expertise like people would,” Rambachan says.
People were also more likely to update their beliefs about an LLM when it answered questions incorrectly than when it got questions right. They also tended to believe that LLM performance on simple questions would have little bearing on its performance on more complex questions.
In situations where people put more weight on incorrect responses, simpler models outperformed very large models like GPT-4.
“Language models that get better can almost trick people into thinking they will perform well on related questions when, in actuality, they don’t,” he says.
One possible explanation for why humans are worse at generalizing for LLMs could come from their novelty — people have far less experience interacting with LLMs than with other people.
“Moving forward, it is possible that we may get better just by virtue of interacting with language models more,” he says.
To this end, the researchers want to conduct additional studies of how people’s beliefs about LLMs evolve over time as they interact with a model. They also want to explore how human generalization could be incorporated into the development of LLMs.
“When we are training these algorithms in the first place, or trying to update them with human feedback, we need to account for the human generalization function in how we think about measuring performance,” he says.
In the meanwhile, the researchers hope their dataset could be used a benchmark to compare how LLMs perform related to the human generalization function, which could help improve the performance of models deployed in real-world situations.
“To me, the contribution of the paper is twofold. The first is practical: The paper uncovers a critical issue with deploying LLMs for general consumer use. If people don’t have the right understanding of when LLMs will be accurate and when they will fail, then they will be more likely to see mistakes and perhaps be discouraged from further use. This highlights the issue of aligning the models with people's understanding of generalization,” says Alex Imas, professor of behavioral science and economics at the University of Chicago’s Booth School of Business, who was not involved with this work. “The second contribution is more fundamental: The lack of generalization to expected problems and domains helps in getting a better picture of what the models are doing when they get a problem ‘correct.’ It provides a test of whether LLMs ‘understand’ the problem they are solving.”
This research was funded, in part, by the Harvard Data Science Initiative and the Center for Applied AI at the University of Chicago Booth School of Business.
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List of Abbreviations | Example, Template & Best Practices. Published on May 23, 2022 by Tegan George.Revised on July 18, 2023. A list of abbreviations is an alphabetical list of abbreviations that you can add to your thesis or dissertation.If you choose to include it, it should appear at the beginning of your document, just after your table of contents.
Abbreviations and acronyms are common in academic writing, but they need to be used correctly and consistently. This web page provides guidelines and examples on how to abbreviate words, phrases, names, and titles in your paper. You will also learn how to avoid confusion and ambiguity with abbreviations and acronyms.
Abbreviations are commonly used in research manuscripts as they can help make highly complex technical writing more concise and easier to read. However, they can also cause a lot of confusion, and make communication unclear if they are not used with caution. This article takes a look at some of the common errors that researchers make in the usage of abbreviations and explains how to avoid them.
Academics often use abbreviations in research writing to meet strict word limits, but this is also where mistakes occur. This article explains the most common abbreviation errors with expert tips on using abbreviations in research correctly. Read on!
How To Use Abbreviations in Academic Writing. November 3, 2022 | Blog Cheat sheet. No time to read? Here's the short version: Avoid contractions like won't, can't, they're, it's.; The first time you mention a phrase that can be abbreviated, spell it out in full and provide the abbreviation in parentheses.
Using abbreviations can be an effective way to avoid repeating lengthy, technical terms throughout a piece of writing, but they should be used sparingly to prevent your text from becoming difficult to read.
Time see Publication Manual Section 6.28 on time abbreviations • Use the time abbreviations shown in the table when they appearwith a numeral. • However, do not abbreviate the following larger units of time, even with numerals: ° days ° weeks ° months ° years Abbreviation Meaning hr hour min minute s seconds ms milisecond Latin see Publication Manual Section 6.29 on Latin
In "Becoming a Ruthless Editor" (Nicoll, 7), I discussed how to shorten a manuscript significantly.One of the suggestions I offered at the end—when the paring down is getting to the critical stage—is to change selected phrases to acronyms.
Examples: PCRs (not PCR's)BACs (not BAC's)Drs. (not Dr's)rbc's (not rbcs)Exception 1: Plurals of some abbreviations, particularly in references, are not formed by merely adding an s.. Examples: p for page and pp for pages (not ps or pgs)l for line and ll for lines (not ls)c for column and cc for columns (not cs)Exception 2: Singular and plural units of measure are abbreviated the same.
In APA, abbreviations should be limited to instances when a) the abbreviation is standard and will not interfere with the reader's understanding and b) if space and repetition can be greatly avoided through abbreviation.
Avoid e.g. and i.e., instead use for example and for instance.. Avoid etc.There isn't really an alternative, so rewrite the sentence. Avoid dept, govt.Use department, government.. Avoid NB, instead use note that.. Avoid vs or v, instead use versus or against (except in Law reports or cases)
Microsoft Word can automatically create a List of Abbreviations and Acronyms. If you use a lot of abbreviations and acronyms in your thesis — and even if you only use a few — there is no reason not to include a list.
What are Abbreviations and Acronyms? An abbreviation is a shortened version of a term or phrase, e.g. kg for kilogram or Dr. for doctor. An acronym is a type of abbreviation constructed from the first letters of a term, e.g. FRP for Fibre Reinforced Polymer or STEM for Science, Technology, Engineering and Maths.
MLA (Modern Language Association) style is most commonly used to write papers and cite sources within the liberal arts and humanities. This resource, updated to reflect the MLA Handbook (9th ed.), offers examples for the general format of MLA research papers, in-text citations, endnotes/footnotes, and the Works Cited page.
Abbreviations Definitions; DNA: Deoxyribonucleic acid: NASA: National Aeronautics and Space Administration: PBA: Process Behaviour Analysis: QA: Quality Assurance
Whether you're working on a thesis or a research paper, abbreviations and acronyms are difficult to avoid in academic writing, which is why it's important that you know how to use them properly. Here's a quick primer. 1. Spell the word or phrase in full at first mention When you first use the term that you
Journal Titles and Abbreviations A Acc. Chem. Res. ACH - Models Chem. ACI Mater. J. ACS Symp. Ser. Acta Biochim. Pol. Acta Biotechnol. Acta Chem. Scand.
Acronyms and Abbreviations. There are various ways of placing acronyms and abbreviations in a dissertation. While using acronyms formed by combining the first letter of each word from a phrase, you should write that phrase in its full form and then write the abbreviation in parenthesis right after that.
The SBL Handbook of Style offers two extensive lists of abbreviations for journals, series, and other standard reference works. The first abbreviation list is alphabetized by source (SBLHS 8.4.1) and the second by abbreviation (SBLHS 8.4.2).If the work cited is in these lists, you may use the standard abbreviation provided.
A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.
Explore popular shortcuts to use Research abbreviation and the short forms with our easy guide. Review the list of 9 top ways to abbreviate Research. Updated in 2023 to ensure the latest compliance and practices
For a complete list of Common Scholarly Abbreviations, please see Section 7.4 in the 6th edition of the MLA Handbook for Writers of Research Papers.. Abbreviations of Degrees. Note: When documenting sources using MLA style, the normal punctuation is omitted for degrees when used in parentheses, tables, works cited, footnotes, endnotes, etc.
List of Abbreviations | Example, Template & Best Practices. Published on 23 May 2022 by Tegan George.Revised on 25 October 2022. A list of abbreviations is an alphabetical list of abbreviations that you can add to your thesis or dissertation. If you choose to include it, it should appear at the beginning of your document, just after your table of contents.
Learn how to write an effective PhD research proposal with practical tips and a clear structure. Understand the importance of a proposal, its key elements, and strategies for presenting your research ideas compellingly. Gain insights to make your proposal stand out and improve your chances of securing admissions and funding.
Before conducting a study, a research proposal should be created that outlines researchers' plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed ...
There are still important disanalogies between our current empirical setup and the ultimate problem of aligning superhuman models. For example, it may be easier for future models to imitate weak human errors than for current strong models to imitate current weak model errors, which could make generalization harder in the future.
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A new research paper has examined all 29,078 US stocks that have existed since 1926 and identified the top 10 performers of all time.. These stocks, some of them household names, have generated ...
People generalize to form beliefs about a large language model's performance based on what they've seen from past interactions. When an LLM is misaligned with a person's beliefs, even an extremely capable model may fail unexpectedly when deployed in a real-world situation.
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