annotation station

notes from articles, podcasts, videos, etc.

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New data discloses flood risk of every home in the contiguous US - Climate Impact Lab

"The data, based on decades of peer-reviewed research, provides the cumulative risk of flooding for more than 142 million homes and properties over a 30-year mortgage."

The Standard for Climate Risk Financial Modeling

We exist to make the connection between climate and financial risk at scale for financial institutions, companies and governments.

[afloweroutofstone]

Emily Lyons vs. OpenAI Foundation (complaint filed in US district court on December 29, 2025)

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"...But [they say] there are disincentives in academia even to spend time disseminating findings to policymakers.

“I’m not tenured, and currently my incentives are to publish within the walls of academia,” [they say]. “You get very few points, and maybe negative ones, for doing policy outreach. You are evaluated solely based on your academic contributions. My time is better spent writing other papers.”"

- Eyal Frank, Sustainable thinking: research aligned with green goals

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Deliberate Once

"Deliberate once, and then don't deliberate again until you get new information that would have changed the result of your deliberation. If you have a big decision to make, set aside some time to do some serious thinking. Ask people you trust for the obvious advice, and then actually do it. Set some five-minute timers, spend time describing the problem before you spend time describing possible solutions, brainstorm a wide variety of solutions. Figure out where you're highly uncertain, find the places where your decision turns on a critical piece of information you're missing, ... Whatever your "think seriously" process is, run it, and then pick the best action available to you (given the information you currently have, having taken into account the incompleteness of your situation). Then do that. Then don't go back into deliberation mode until you encounter information that would have actually changed your answer. If you do it right, there's no need to go back to worrying about which thing you should be doing unless you encounter new evidence or information. When you do, deliberate again — or, better, plug the new evidence into the model you built when you deliberated the first time, instead of re-doing all that work. Half the reason for really deliberating hard the first time is to build a versatile model, anyway. (Though of course, evidence and experience will also cause you to update that model as you go.)" (x)

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Kegan's Stages of Development

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narcissism of small differences

"the more a relationship or community shares commonalities, the more likely the people in it are to engage in interpersonal feuds and mutual ridicule because of hypersensitivity to minor differences perceived in each other.

in a loving relationship, there can be a need to find, and even exaggerate, differences in order to preserve a feeling of separateness and self.

consumer culture ... as predicated on the narcissism of small differences to achieve a superficial sense of one's own uniqueness, [a] sense of otherness which is only a mask for an underlying uniformity and sameness."

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Advice on pursuing data science in the public interest

"... most junior data science roles at non-profits and policy research institutions don’t need the cutting edge of data science technical skills. Some of those skills will be important, but in the public sector, a meaningful contextual understanding of your data and domain is guaranteed to be important. ... to be successful as a young data scientist in the public interest— [you need] priorities that are driven by the specifics of a policy domain.

develop depth in a [specific policy] domain over breadth in data science

there is an enormous amount of free information on the internet [when it comes to learning data science.] Yet, this makes it much more difficult to choose what skills are important.

My advice is straightforward:

In the early days, don’t try to learn everything. Instead, focus on a specific area of policy or service delivery, and let that drive every other decision you make.

Pick a domain you’re interested in, and then be the best data scientist you can be in that area. Practically, this means spending more time understanding relevant data sets, more time understanding the data collection processes used in your field, more time reading relevant research, and more time doing applied work ... [This also comes at the cost of] reducing time spent learning a more diverse set of technical skills and statistical methods. In the short term, this is a worthwhile trade-off.

At most public service organisations, just having the best technical skills will rarely make you the most qualified applicant for a job. The best candidates are typically going to have a strong overlap of content knowledge and technical skills. So, this strategy is meant to make you highly competitive for a small number of jobs, rather than generally employable. This might sound risky, but done well, it should give you more control over what you do. You’ll be able to take your pick of a few jobs in your field, as compared to a general-purpose programmer and statistician, who will have to send out more and not-as-well-targeted applications.

The most common response that this advice elicits from students is that they don’t know what domain to pick, since they don’t have much experience in anything specific or aren’t yet very passionate about any one area. That’s understandable, but I still think you should choose something anyway.

First, you aren’t locked into your choice forever. There is plenty of overlap between various fields of public policy, social science and non-profit service delivery. Whatever you choose can get you started and will likely stay valuable in the long-term.

Second, in my experience, it’s unusual to be especially passionate about any specific issue until you’ve worked on it extensively. For the typical public servant, passion isn’t automatic, it’s earned. Dive into the papers, the debates, and the datasets in a subject and give it some time—you’ll be surprised how quickly you learn to care about the obscure nuances of your field.

Spend your time on applied projects in your domain

Working on applied data projects, in which you might conduct a complete data analysis, build a new dataset or develop a data tool, is extraordinarily valuable. You should opt into this kind of work (in classes, internships or independently) as often as possible. [It enables you to]learn about relevant data, increase your knowledge of the field, and improve your technical skills all at the same time. Your ability to conduct an applied project from start to finish is also the strongest signal you can send to an employer. It’s not just a claim that you can do the job, it is the job.

Knowing where to begin can be intimidating, so don’t be afraid to start simple. Downloading a dataset, performing basic data cleaning, merging it with another data set and then doing descriptive analysis with some charts is a great start.

Know your data

Understanding the universe of data that is relevant to your field is an invaluable skill. Take it as seriously as learning to code.

First, try to build an understanding of what data is out there. Start a list of datasets used in the analyses of your field and add to that list over time.

Suggested resources:

government open data websites 

Google Dataset Search

You should work with this data as much as possible and take notes to yourself about the data. This also means reading the data documentation—one handy thing about government and non-profit data is that there is frequently pretty good data documentation. Generally, know that you do not understand any dataset until you have read the documentation.

You should also look out for public critiques and comparisons. You might be surprised by how much is written on announcing, critiquing and comparing different public datasets (these links are from empirical conflict studies). For proprietary data, do informational interviews with data analysts in your field and ask them about the datasets they are working with.

You should also deepen your understanding of data collection processes. While you can develop good questions about your data’s collection from working with it, you must go elsewhere to understand its origins.

Look at the forms (oh how they change) and surveys that generate government administrative data. Consider getting in touch with the curators, especially once you have questions from your exploratory analysis. In some cases, you may even be able to directly observe the data collection process. This might mean going door-to-door for a survey or volunteering as a monitor for some process (e.g. voting or standardised testing).

This is a lot of work, but it will improve your work and distinguish you as a young data scientist.  I think most senior data scientists would agree that understanding the shortcomings of specific datasets is a compelling and rare signal of analytic maturity.

Let your domain choose the statistical methods that you learn

There are too many statistical methods. Learning them all is not a remotely achievable goal. Even worse, aiming to learn as many as possible will undermine your effectiveness as an applied data scientist. Instead, I’d argue for two goals.

First, understand the broad typology of data science methods and what questions they can answer.

Second, learn how to learn, and continually develop your skills while performing applied data science projects.

I’ve written before about the scope of data science methods that are useful in policy analysis, but only one is universally necessary: causal inference. You need to understand causal inference methods. Even if you don’t use them yourself, you need this knowledge base to read the relevant social science in almost any field.

After that, you want to know enough about methods to know what questions they are designed to answer. Is there a meaningful prediction I can make with supervised machine learning? Are there latent groups that I could discover with unsupervised learning? Is there an intervention I could simulate outcomes for?

To decide what else to learn in depth, your decision should be driven by your domain. For instance, if you want to study international development, there is a long history of randomised experiments, and a more recent prominence of satellite imagery. If you want to study political science, social media platforms have made an understanding of network analysis and natural language processing far more valuable. Personal devices are creating trace data that adds a critical geospatial component to many social science questions, especially combined with survey research. Academic research and Twitter are great ways to get exposed to what’s going on in your field and can help you narrow down the wide world of data science into a manageable number of methods to learn.

A brief aside about language choice

On programming languages, the options are clear: choose either Python or R. I prefer R and think it’s better for causal inference methods / econometrics and data visualisation, which are both important here. That said, Python is a perfectly good choice, and is more versatile in working with the internet and some engineering tasks. These differences are not so important for you to dwell on it.

More important than which language is that you obtain depth in one. Learning both is valuable in the middle- and long-term, but in the early days, your ability to execute on projects is paramount. Since any given project is likely to be mostly in one language, your ability to contribute will be much higher if you have a robust set of skills ready for that language. This isn’t an argument against being a ‘polyglot’ programmer, or having breadth in a range of frameworks, but that should be later goal for aspiring data scientists.

Wrapping up

None of this is an argument against undirected learning or eventually developing breadth in data science methods—both of which I endorse. I simply want to offer a framing for how to prioritise what you learn in the early stages of your civic data science career.

There are some skills you can’t avoid (the Linux command line, git, and don’t skimp on communication skills like data visualisation, literate programming and writing), but otherwise, use a domain to help you focus your efforts. In terms of getting your first civic data science job, you’ll have an easy and cohesive narrative to market yourself, and you will benefit from having demonstrated interest in a domain, rather than the all-too-common claim (“I am very passionate about…”) that haunts cover letters.

[your] analysis—and your impact—will be all the better for it too."

Uncommon advice on becoming a data scientist in the public interest

Civic data scientist Alex Engler shares his insights for those aspiring to work with data in the public sector.

[funkymbtifiction]

How I Experience My Ni

SUBMITTED by lover-of-grey-matters

Note 1: This is how I experience my Ni; it does not have to fit to everyone’s. Ni is an introverted function and thus, subjective.

Note 2: My description of Ni is going to be a little vague. I think dominant functions are the hardest to describe for anyone, it’s like the air - you are so used to breathing that you forget it exists and find it hard to make note of it. How Ni works: The myth is that Ni just ‘knows things without knowing’ and ‘is always right/precise.’ This is not true. Ni has a very solid base for the projections it conjures – the objective, wide-breadth extroverted sensing. Se collects every information indiscriminately and in volumes. Then Ni filters the data into projections/patterns.

I have previously compared Ni to a high-throughput chromatography machine – input a myriad of molecules with the cell extracts, and it will output the molecules you only need. The point is, Ni is not magical. It establishes patterns from a given dataset. High Ni users are less aware of the data collection process and thus can’t always trace the pattern back to the data, making it look like a ‘gut feeling.’ Furthermore, the part that the high Ni users are conscious about, the Ni itself –  it too is abstract and subjective and hence, can be hard to verbalize. This further adds to Ni’s mystique.

So once again, to the people who do not understand how chromatography works, the machine may seem phenomenal. But that does not make the machine itself mysterious. It operates on a very simple principle, it just appears mysterious. Ni and doing things: Extroverts have an extroverted function as dominant, which means they are quick to act and take charge (particularly Te and Se in my experience). People with a dominant introverted function need to step back and consult their dominant function first before engaging with the external world. This can be consulting whether it aligns with their internal values (Fi), or dissecting the whole deal piece by piece to understand all of its constituents (Ti), or accessing own personal sensory library for information (Si).

Ni-doms will go inwards first, except they won’t be seen actively doing something. They just sort of incubate for a while, then start doing it and they usually do it to perfection. Once again, it looks mystical, but it is not. During the incubation phase, our mind warms up and projects patterns, then taps all of those patterns for the best possible outcome and selects it to unravel a long-term plan. Once we start working, we act on the plan, which is very tangible to us. We can visualize the end from the projection our Ni has made and we simply continue to walk forward to it. It looks like the incubation phase does not have any 'productive’ output, but for Ni-doms, to sit on something without doing anything is not important, it’s crucial.

For example, say I have something to write, maybe the literature review part of my thesis, or maybe just a post for this blog. For a while, I won’t do anything. I will trifle with some things and that’s it. But the ideas will be there, just not in the foreground. It’s a bit like a background music, it’s there and it sets the stage for the plot to follow. Then I will write something at one stretch, and it won’t need any editing or proofreading.

Because the Se-Ni thing is subconscious, I think Ni-doms rely a lot on their dreams and visions. I have countless times went to sleep thinking about a problem and woke up with a solution. And I am not alone, my brother is a tert-Ni and Ti-dom. He often wakes up with a new game plan for chess or a solutions to the math problem he had been pressing. Ni and symbolism/puzzle: Ni-doms don’t always talk in symbolic languages. Actually I think it’s a bit hard for us, given how 'personal’ our symbolism is, we find it hard to explain. Neither do I love puzzles very much. The symbolism is part of our worldview, not our expression. An example of this is the book Memoirs of a Geisha. Sayuri’s worldview is Ni, the water imagery with herself and such. She is not trying to express things through metaphors and similes, she things of the world in terms of those symbols. This is the same for me. I think of things is terms of what they represent. But unlike an Si user, there’s no sensory trapping to them.

Ni and perception: changing our worldview is hard for us. It’s not impossible, it’s just 'costly.’ We have to go though a lot of questioning and re-questioning. This is true for the perception bit obviously. When it comes to our verdicts or judgments, we are more flexible.

Elizabeth Bennet (ENFP) has hard judgments, but her perceptions can change very quickly. The process in opposite for an Ni-dom. Again, Sayuri’s worldview/manner of perception is hard to change – she goes through war and poverty and settles in America and still has the same worldview she did back in Gion. However, her judgment about any people (like Nobu-san, Mameha) is very flexible and open-to-change. Ni myths: Ni is not perfection, just a manner of perception. Being Ni-dom does not make you smart/creative/wise/interesting/deep by default. Ni-doms can by dumb and boring if they don’t channel their functional stack to usefulness, which is true for every other functions. They canbe  delusional if they lack Se input. An example of shallow Ni-dom with countless mistaken interpretation is Melisandre from A Song of Ice and Fire. That’s what I think of my Ni, and it does not have to universally true. I would love if someones adds to it.

Mod Note: Anal editor coming out in me, but even Ni-dom writers need proof-readers and editors. You ain’t perfect. ;)

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Don't over-rely on your IQ score to inform life decisions/outcomes.

"things that are statistically true aren’t always true for any individual.

IQ is some complicated central phenomenon that contributes a little to every cognitive skill, but it doesn’t entirely determine any cognitive skill.

[High levels of success when you have an average IQ] is not quite as likely as if you have a high IQ, but it’s very much in the range of possibility. And then you add in the effects of working hard enough, and then you’re getting somewhere." (1)

"On a population level, we see that the average doctor is 30 IQ points higher than the average janitor, that college professors are overwhelmingly high-IQ,

But on an individual level, we see that below-average IQ people sometimes become scientists, professors, engineers, and almost anything else you could hope for.

You can read about IQ, or heredity, or stereotypes, or gender differences, or whatever, and you can say – ah, there’s a slight tendency for one thing to correlate with another thing. ... If you don’t get that, then the world is terrifying.

correlations are neither meaningless nor always exactly 1.0.

Use IQ to explain and predict social phenomena. Work on figuring out how to raise IQ. Assume that raising IQ will have far-ranging and powerful effects on a wide variety of social problems. Just don’t expect it to predict a single person’s individual achievement with any kind of reliability. Especially not yourself." (1)

https://slatestarcodex.com/2017/09/27/against-individual-iq-worries/

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planning fallacy

we are likely to underestimate the costs of a project, such as how long it will take and how much it will cost.

Why it happens

positivity bias. The human brain is generally biased towards positivity, leading us to make overly optimistic predictions about our projects, + disregard information that contradicts our optimistic beliefs.

anchoring. Once we have set unrealistic plans, other biases, such as anchoring, compel us to stick with them. Pressure from team members, superiors, or shareholders to get things done quickly and smoothly also makes it more costly for us to revise our plans partway through a project.

How to avoid it

incorporate outside information into the planning process rather than relying solely on intuition.

implementation intentions. creating a specific plan (time, location) to do the thing; envision oneself doing it

segmenting large projects into smaller subtasks to generate more accurate estimates of time/costs.

https://thedecisionlab.com/biases/planning-fallacy

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"Sexual Fours often have severe doubts about their own desirability, so they strive for accomplishments that will make them acceptable to the other ... while being resentful of those who achieve those things. Envy is also most clearly visible in this variant. Relationship problems arise because Sexual Fours often become romantically involved with people who have qualities that Fours admire or want in themselves, but then end up envying and resenting the loved one for having these qualities. Idealizing the other can quickly shift to rejecting them for their slightest flaws. At the same time, Sexual Fours are often attracted to people who are, for one reason or another, unavailable. 

Unhealthy Sexual Fours unconsciously live by the adage "misery loves company". ("If I'm going to suffer, so are you.") Sexual Fours may create competitions and rivalries and feel completely justified in undoing their opponents or in hurting those who have disappointed them.

They are prone to rapid shifts in their feelings toward others, even toward their protectors and loved ones. Their emotional chaos may lead them to rash acts of violence against themselves or the people they believe have frustrated their emotional needs." (x)

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fallacy of personal validation (aka Barnum effect): the tendency to believe that vague predictions or general personality descriptions, such as those offered by astrology, have specific applications to oneself. (x)

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Default mode network (neuroscience)

tl;dr: The default mode network (DMN) is responsible for the self-aware/self-conscious part of our brain. Sometimes, depression/shame arises from being too self-aware, too conscious of our personal narratives, too prone to attaching meaning to events/stressors.

It is best known for being active when a person is not focused on the outside world and the brain is at wakeful rest, such as during daydreaming and mind-wandering. It can also be active during detailed thoughts related to external task performance.  Other times that the DMN is active include when the individual is thinking about others, thinking about themselves, remembering the past, and planning for the future. The DMN creates a coherent "internal narrative" control to the construction of a sense of self. The default mode network has been hypothesized to be relevant to disorders including Alzheimer's disease, autism, schizophrenia, major depressive disorder (MDD), chronic pain, post-traumatic stress disorder (PTSD) and others. In particular, the DMN has also been reported to show overlapping yet distinct neural activity patterns across different mental health conditions, such as when directly comparing attention deficit hyperactivity disorder (ADHD) and autism. Rumination, one of the main symptoms of major depressive disorder, is associated with increased DMN connectivity and dominance over other networks during rest.  Such DMN hyperconnectivity has been observed in first-episode depression and chronic pain. Altered DMN connectivity may change the way a person perceives events and their social and moral reasoning, thus increasing their susceptibility to depressive symptoms. Lower connectivity between brain regions was found across the default network in people who have experienced long-term trauma, such as childhood abuse or neglect, and is associated with dysfunctional attachment patterns. Among people experiencing PTSD, lower activation was found in the posterior cingulate gyrus compared to controls, and severe PTSD was characterized by lower connectivity within the DMN. (1)

https://en.wikipedia.org/wiki/Default_mode_network

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loneliness and trauma as causes of hoarding

"Individuals with OCD or hoarding symptoms frequently report experiencing traumas and traumatic events may be a risk factor for anxiety and mood disorders

Hoarding severity was positively associated with number of traumas before symptom onset. ... Hoarding severity was positively associated with the number of traumas that occurred prior to symptom onset, supporting the notion of cumulative trauma in hoarding.

Exposure to stressful life events increases unwanted intrusive thoughts, such as obsessions and can condition anxiety to specific stimuli, leading to increased reliance on behaviors, such as compulsions, that reduce anxiety in response to these stimuli." (x)

"We hypothesized that excessive object attachment is an attempt to compensate for unmet relatedness needs. ... Object attachment might be an attempt at compensating for loneliness. ... Further investigation may be warranted into the possibility that addressing loneliness in HD might result in lower object attachment. (x)

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non-verbal communication & genetics

Non-verbal cues include: facial expressions, gestures, body language, eye contact, appearance

"individuals with a higher genetic inclination toward emotional intelligence or empathy may be more adept at recognizing subtle non-verbal cues, leading to better social interaction and understanding. ... Additionally, [serotonin], which affects mood regulation and social anxiety, can influence how comfortable individuals feel in social situations, affecting their non-verbal expressiveness." (1)

"In order to achieve competency in social interaction, we need to have social cognition, social motivation, social awareness, and skills in maintaining relationship with others. ... oxytocin (OXT) [and the the OXT receptor (OXTR)] plays a central role in many aspects of social behavior," (x) "The oxytocin receptor gene (OXTR) has been linked to social bonding, emotional recognition, and the interpretation of non-verbal cues"

GenomeLink report

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Among four twin studies examined in 2003, the mean percentage for genetic influence for each of the Big 5 personality traits:

openness to experience: 57%

extraversion: 54%

conscientiousness: 49%

neuroticism: 48%

agreeableness: 42% - Wikipedia, Big Five personality traits

[infjedi]

Can u explain the ENFP Te bitch slap please?

You know, Personality Growth  already did such an amazing job at this, that I will just share article: 

What Is the ENFP Te Bitch Slap?

The ENFP Te Bitch Slap is an outward attack towards another person. This attack is made using facts and logic that the ENFP has collected in their mind. They have come to the realization that someone has wronged them intensely, often emotionally wounding or hurting the ENFP will cause this to occur. This can also occur when the ENFP sees that someone has hurt or wronged another person. The ENFP is using a rather strong sense of righteous indignation to fuel their attack on another person. This is often done to ward off further hurt for the ENFP, as a means to making this person realize they were wrong. The ENFP is bypassing their emotional connection to this person and is no longer sensitive to their feelings in that moment. They internally feel like their attacker has done something deeply wrong, causing the ENFP to attempt to make this evident to the other person. They use their collected facts and information as a way of tearing down the other person’s argument. They will bring up as many facts as are necessary so that they can prove this person entirely wrong. The ENFP will aggressively and straightforwardly tear apart this person’s argument, finding ways to show them that they are wrong.

This sometimes occurs when someone has outright hurt the ENFP, or when another person has crossed a line. The ENFP may attempt to draw clear lines for people, but when they continue to cross them they will definitely use the Bitch Slap method on this person. The ENFP feels like this is a necessary way to get their point across, especially when they feel like someone is not hearing them clearly. This is often a way of forcing others to respect the ENFP, when they feel like they aren’t properly doing so. They are caring and giving individuals, but they become frustrated when people are crossing lines continuously. Even though the ENFP is a positive and affectionate individual, they are capable of becoming angry. They dislike when people are doing something that they deem as wrong, especially when someone is blatantly being disrespected. The ENFP often believes that their Te Bitch Slap reaction is a necessary way to make this disrespect end.

The ENFP has essentially perceived a wrongdoing and uses their sense of Te logic to make this known to the person doing said wrong. They feel as though teaching this lesson is extremely important, so they take matters into their own hands. When the ENFP is preparing their attack, they feel like it is the right thing to do. They definitely believe that it is very necessary to express their anger and give specific reasons why they feel this way. The ENFP often delivers their speech in excruciating detail, with cataloged facts and information.

What Does The ENFP Te Bitch Slap Look Like?

How to recognize the ENFP Bitch Slap is rather simple, since it is very unusual for the ENFP to act this way. They become very clear in their anger towards someone, and it can be rather frightening to witness. The normally bubbly and considerate ENFP, no longer cares about hurting someone else’s feelings in that moment. They will probably feel intensely guilty when the bitch slap is over, but in that moment they feel like it has to be done. They are essentially righting a wrong that has been done to them and the ENFP feels that this is necessary. This is a rather shocking explosion of logic driven anger that causes the ENFP to look much like an exploding volcano.

The reason that this Bitch Slap can be rather painful for others, is because it can be rather accurate. The ENFP is capable of remembering things that will probably cause the other person to feel completely exposed. The ENFP has cataloged information that can very easily leave the other person feeling frustrated and upset. Their Te attack often exposes information that will cause the other person to become very upset and hurt. They will most certainly hear what the ENFP has to say, since they have given them no choice. The ENFP understands people very well, making them capable of using this against others. They know exactly what to say to emotionally affect someone easily. This causes their words to cut likes knives, making the other person feel momentarily shocked and upset. The ENFP will also use information to make the other person understand that they have crossed a line. The ENFP is hoping that this will prevent the wrong doing from happening in the future. This is an onslaught of factual attacks, using information and data to explain why the other person is wrong. The ENFP is no longer using their emotions or considerate self to communicate, but is rather using data only. Their delivery is often lacking emotional connection, attempting to deliver it in a dispassionate manner. This is an often harsh critique of the other person, which can appear very cold and hurtful.

The Aftermath

Since the ENFPs actions often escalate to a full on attack against the other persons moral character, they often feel very guilty afterwards. In the moment the ENFP perceived a wrongdoing that they needed to rectify somehow. They go into a complete mode of tearing down the other person so that they can show them what they have done was wrong. The ENFP can be so zoned into what they are doing, that they often regret it afterwards. The ENFP may still believe that the other person was wrong, but they feel bad for how they delivered their explanation of the wrongdoing. The ENFP will often apologize a few days later, when they are back to their usual selves. They want the person to realize that they were upset, but that they didn’t mean to hurt them because of it. ENFPs do care deeply about people, so they often feel bad about their harsh delivery in the moment.

People often expect the ENFP to still be angry afterwards, but they often are not. They have already done what they believed was right, and have expressed their anger towards the other person. The ENFP doesn’t feel the need to hold a grudge over what happened, feeling like it has already been rectified. This Bitch Slap is often truly over once it ends and the ENFP is capable of moving on from it. They simply wanted to make sure that the other person understood that what they did was wrong.

[highonmbti]

Accurate.

[w-ht-w]

Accurate.