In today’s fast-moving, AI-powered era, autonomous agents are playing a bigger role than ever. They are helping businesses run smoother and making decisions affecting millions of lives every day. While these systems are designed to make our lives easier and unlock new opportunities, we can’t get carried away—we need to implement proper AI Agent Evaluation frameworks and best practices to ensure these systems actually work as intended and follow ethical AI principles.

most financial models described in the literature come from the corporate world, putting the need to maximize revenue in tension with higher education’s mission-based goals that are harder to quantify

Implementing relevant data metrics and making these available to users.

It was created in 2001

4,463,574

2,400,000

ORCID was first announced in 2009

The developer and administrator of the DOI system is the International DOI Foundation (IDF), which introduced it in 2000

2,340,117

To use open infrastructure consistent with your organization’s values.

The progress and impact of the project will be measured and monitored through the collection ofquantitative indicators. The different systems of the project partners as well as ORCID Inc. andROR will be queried. If possible, indicators for all 10 PID use cases should be measured. Theseinclude for example the following indicators:● Number of registered DataCite DOIs by scientific institutions in Germany.● Number of registered DataCite-DOIs that have a link to further resources via arelated-IDentifier relationship.● Number of ROR implementations at scientific institutions in Germany.● Number of GND records that have an ORCID iD or a ROR ID.● Etc.

They are efficiency and effectiveness. For memory systems, an effective system is one that gets the right answer every time no matter how long it takes you. And the efficient system is one that uses the least amount of resources like time, associations, dependent systems, etc. but it may not be that good at providing the correct answers.

there's one company that i advise called inside tracker

The “Goals, Signals, Metrics” framework is the most important thing I learned from Ciera, while at Google. This is a framework for defining metrics:Define the actual goal you’re trying to accomplish. Opt for a descriptive definition, for example, say “here is a description of what we want to actually accomplish with our work.” Not the vaguer, “I want to measure X.”Define signals. How would you know if you accomplished that goal, if you had infinite knowledge of everything? These are called “signals.” For example, a signal is “how happy are people with my product?” You cannot directly know how happy people are with your product, unless you’re magically all-knowing. However, if having happy customers is one of your goals, then this is the right signal for that.Figure out your metrics. These are proxies for that signal. Metrics are always proxies, there are no perfect metrics.

Defects found in peer review are not an acceptable rubric by which to evaluate team members. Reports pulled from peer code reviews should never be used in performance reports. If personal metrics become a basis for compensation or promotion, developers will become hostile toward the process and naturally focus on improving personal metrics rather than writing better overall code.

K-Anonymity, L-Diversity, and T-ClosenessIn this section, I will introduce three techniques that can be used to reduce the probability that certain attacks can be performed. The simplest of these methods is k-anonymity, followed by l-diversity, and then followed by t-closeness. Other methods have been proposed to form a sort of alphabet soup, but these are the three most commonly utilized. With each of these, the analysis that must be performed on the dataset becomes increasingly complex and undeniably has implications on the statistical validity of the dataset.

The general trend is that students who report improved socioemotional outcomes also show suggestions of increased activity in collaborative tools relative to their peers.

In this sample, 1,868 students enrolled in at least one undergraduate class with, and at least one undergraduate class without, some form of collaborative activity (peer review, Piazza, CourseNetworking, etc.), not including discussions.

Similarly, social annotation tools such as Hypothesis provide opportunities for students and instructors to interactively engage in a shared resource of interest wherein problems, challenges, and insights can be discussed.

We estimate that students performed 1.16% points (95% HDI [0.65–1.66]) better in their undergraduate courses with collaborative activities, compared with the same students’ performance in undergraduate courses without collaborative activities.

Teaching with social reading doesn’t mean peering over students’ shoulders. Rather, teaching with social reading should help students share and connect.

“It’s really hard to help Emmett understand anything qualitative,” one former employee says. “It has to be quantitative.”

Employing an evidence-based methodology, CitiIQ has created a comprehensive, objective measurement of a city.

um kevin anderson 00:12:43 if you can talk more about this issue both you and george assad raymond and so many other climate activists talking about this issue of wealth 00:12:55 you say per capita is a flawed metric as most polluting industries have been moved to developing nations so it's not reflective of the rich nation's emissions take all of this on 00:13:09 yeah i mean that's a really key issue and i think if i focus in here on the uk where i know it's a place obviously i know much better that what we've done in the uk we've closed down a lot of our industry and then we import the manufactured goods from elsewhere in the 00:13:22 world and then we turn around to those parts of the world and then we blame them for the emissions in manufacturing the goods that we are enjoying and that's everything from our electronic goods to parts for our cars as our clothes so you know the uk is 00:13:35 effectively moved to a bar and banking culture and and and offshore virtually everything else and so we when we looking at our total amount of emissions we have to take account of the carbon footprint of our lifestyles and that 00:13:47 does include the emissions that we associated with things that we import and export i mean you take that into account you tend to find that most wealthy countries have a much larger carbon footprint than when you just look at the energy they use within their 00:14:00 boundaries and i think it's really key again when we think about these issues of equity we we that we take this what's often referred to as a consumption-based accounting method we take that into account because it is unfair to be 00:14:12 penalizing poor parts of the world for them making things to help us have a better quality of life over here and when we do that then the challenges get even more striking in terms of what we have to do and it also also brings out 00:14:25 even further the issues of equity the disparity between the richer parts of the world and the poorer parts of the world but i also think on the equity point it's really worth bringing out that it's not as if everyone in the uk is even 00:14:37 there isn't just one public in the uk there are multiple publics there were those of us who are the wealthy ones in our own country that are responsible for the lion's share of missions within the uk that will be true chain for the u.s for germany for japan australia and so 00:14:50 within all of our countries there are large swathes of the country who are the average and below average consumers and for them the response to climate change is very different from those of us who are in our own countries are responsible for the lion's share of 00:15:03 emissions so i think we have to differentiate not just between countries but even within our countries and my concern there is that who are the people that frame the climate dubai debate they're the climate scientists and the academics they're the 00:15:14 entrepreneurs the business leaders the journalists the barristers they're all the people that are in the very high emitting category so we frame the debate and we never ever frame the debate with equity at its core and with regardless 00:15:26 of our maths or our moral sorry regardless of our moral position the maths tell us if we are to deliver on the commitments then equity has to be a key part of our responses but we never talk about that because we are in that 00:15:38 high emitting group

Note also: this incentive is in fact far more hard-headed than any metric of hedonic economism—such as GDP, which is measuring the amount of desire satisfied by the productive sector. At best GDP is a revenue metric. A prudent manager will manage an enterprise to maximize capital and profit, not revenue.

Lately, metrics related to social usage and online comment have gained momentum — F1000Prime was established in 2002, Mendeley in 2008, and Altmetric.com (supported by Macmillan Science and Education, which owns Nature Publishing Group) in 2011.

The urgent argument for turning any company into a software company is the growing availability of data, both inside and outside the enterprise. Specifically, the implications of so-called “big data”—the aggregation and analysis of massive data sets, especially mobile

OKRs in Product Management

From my perspective this would at least require a deep change in how we measure value, define labor and organize the financial system.

We’ll make sure that decisions that need to be made post-launch are informed by actual facts of user behavior, not just best guesses.

Short-term (i.e., “This year, I will see...”) and long-term (i.e., “In 10 years, I will see...) indicators are needed.

Amanda Matos - Métricas & DevOps - Por que você deve medir para conquistar?

For many years, academia has relied on citation count as the main way in which we measure impact or importance of research. As a result, citation count is one of the primary metrics used when evaluating researchers. Citation counts also form the basis for other metrics, most notably Clarivate’s Impact Factor as well as the h-index, which respectively evaluate journal quality/prestige and researcher renown.

these are not the only reason behindthe trends observed. An examination of the peaks

Wikidata quality assessment

Ontology depth

sed in the present analysis

We used the following keywords:‘ontology metrics’, ‘ontology evaluation framework’, and ‘ontology evaluation’. From the results,we selected only papers including primarily structural metrics.

We calibrate the model for 6 countries at various stages of economic development: 3 low-incomecountries (Uganda in 2005, Kenya in 2006, and Mozambique in 2006), and 3 emerging marketeconomies (Malaysia in 2007, Philippines in 2008 and Egypt in 2007).

In the model, agents are heterogeneous { distinguished from each other by wealth and talent.Individuals choose in each period whether to become an entrepreneur or to supply labor for a wage.Workers supply labor to entrepreneurs and are paid the equilibrium wage. Entrepreneurs haveaccess to a technology that uses capital and labor for production. In equilibrium, only talentedindividuals with a certain level of wealth choose to become entrepreneurs.

The Solow–Swan model augmented with human capital predicts that the income levels of poor countries will tend to catch up with or converge towards the income levels of rich countries if the poor countries have similar savings rates for both physical capital and human capital as a share of output, a process known as conditional convergence.

and using five-year averages of all variables to smooth out cyclical variations

Maybe not a ELI5, but: Moments are expectations of things. E(X) is often called the "first moment," E(X2 ) is the "second moment," etc. They can also be more complicated, like E(exp(5x+y)), or whatever. In econometrics, you're trying to figure out something about the underlying distribution of your y's and your x's (and the errors). Often you don't know the shape of the distribution, but you know some moments of the distribution. This is useful because you can't use maximum likelihood estimation unless you make assumptions on the entire distribution. With ordinary least squares, you assume that E(ex) = 0, that is, the errors are uncorrelated with the regressors. You can write e = y - xbeta, to get a moment condition E(x(y-xbeta)) = 0. If you do GMM with this moment condition, you get the regular OLS estimator. If you have endogeneity of some kind, you don't know that E(ex) = 0, but you might have some instruments Z, such that E(ez) = 0. This gives you the moment condition E(z(y - x*beta)) = 0. GMM is nice because it makes relatively weak assumptions compared to other ways of estimating parameters. I hope that helps!

proportion of youth and adults with information and communications technology (ICT) skills, by type of skill’ (SDG 4.4.1)

Develop appropriate measurement and monitoring strategies

it shows the six degrees of separation.

1000 assignments in the assignment bank and 11 thousand submissions

The first great experiment was UMW Blogs, our institutional blogging system which debuted in fall of 2007. In that nine years, it has had almost 13,000 users and it now contains 11,000 individual WordPress sites.

(Among the recommendations: Greater emphasis on visuals, greater variety of formats and voices. They also announced that the Times would be introducing an alternative metric to pageviews that would “measure an article’s value to attracting and retaining subscribers.”)

We’ll let you know who made the millionth annotation

PLOS Labs is working on establishing structured reviews and we have talked with them about this.

I think it is possibly too early to tell.

based on a scientific analysis of citation data

metrics on annotations/comments

Don’t guess at what’s wrong with your infrastructure–graph it.

They also adopted the mantra, “If it moves, graph it.”