Thanks, I'm still working on the data engineering so it can be accessible to open data/science. I've got another few months to contribute.

Raw counts and geolocations are helpful for law enforcement and "critical time-sensitive social program interventions" ie: tactical short-term program funding.

I

Totally agree. I really try to honour the individuals I know it looks like rows from data table. I'm always aware that each row is a child who is afraid, hurt and in need of TLC.

It's hard work form me. I cry often. But after 30 yrs of making people rich from data, this feels better for me.

I work with quantitative data only. I don't do lit reviews and book report type research. Much of it is rehashed and derivatives if not just conforming (easier to get funding).

I felt my son's insight, while admittedly a generalization, helped me open up my perspective which helps me ask more meaningful questions.

There's no precise approach to understand individual outcomes but, in aggregate, looking at abuse through a public health/public safety perspective, the more likely we are to identify and support victims while securing better evidence against perpetrators.

Totally appreciate your perspective and your devotion to helping kids in need. Sincerly, thank you!

At about 15, my precocious kid told me this about the boys at school who were having problems -

The aggressive knuckle head kids that are getting into fights tend to have had abandonment / absentee father stuff.

The quiet self-destructive kids - not aggressive but often intoxicated with whatever as often as possible. He said the kids that are dragging themselves around and are self-sabotaging are the ones with the mums who discarded or neglected them.

It seemed like a really insightful "ground truth". What are your thoughts, having lived with some of the kids?

Follow the glitter!

I can't answer that from my work. If you want to play with the data, you can sign up at Statista for free and get spreadsheets you can smoosh around.

Smoosh, squish and grind aren't official DS terms, but go ahead and play.

I'm just daylighting abusers of children, starting with the most likely to harm.

Thanks. I work strictly with large-set open data. I don't do book report research as much of it is from a methological echo chamber. I let others debate that stuff.

Lots of synthesis of "existing literature" involving unrepresentative sample size and very, very laggy reporting.

I know in Canada, the government data science talent pool is extremely thin. Their output is known to be really slow and lumpy, generally using deprecated technologies.

In my country, we're still wrapping our heads around our indigenous genocide (in progress). The colonist thugs involved were teachers, social workers and bureaucrats. These have perpetuated lies for 200 yrs. It'll continue as long as we like mineral rights.

Despite federal open gov mandates, the Canadian data is but a trickle of molasses in winter.

Can't concur with your analysis. The bias was part of legal guidance to judges called "Tender Years Doctrine".

Check out "Tender Years Doctrine" in the US.

You should look into *** Tender Years Doctrine *** that instituted arbitrary gender bias in child custody. Fathers were / are routinely separated from their children with wide legal and institutional support.

Some states changed this legal default as recently as 2016 (needs fact checking).

The doctrine's bias is well known and documented as being a critical factor of enabling abuse in plain sight as you put it.

Thanks for taking the time to check it out.

That's why I like Data Sci - unarguable facts can daylight the abusers.

Covid isolated children with their abusers. Expect to see more of this stuff under a public health lens.

It's like those studies (and PSA campaigns) years ago confirming violence against women is mostly from their partners. In this case child abuse, likewise is more likely from a mother.

Thanks for caring about facts enough to check the data. Keep it coming!

Can you point to credible data for that, please? Doesn't matter what country as long as the sample size is over 200.

Not at all anecdotal. Quantitatively evident. It's gov't data from the US. You can examine the data and the methodology and even the data to have a go at it for your own peace of mind.

​

**Definitely hard facts here. No cultural wishy-washy perceptions or anecdotes - just gov't processing data. **

If you're on this sub, you'll probably like Statista. I'd recommend you sign up, it's free for basic functions. You should be able to download a spreadsheet and have go... but we might have different hobbies 🤓😎😅

UML is a powerful design option that can be used for a lot of applications involving objet data.

Marketing types call these character maps "stakeholder maps" and they can be weighted based on the nature of the plot. When that happens they're sometimes called "heatmaps". They're very helpful for outlining the landscape before planning a strategy.

Basically, you did a professional piece of work here.

Nice work. There's real applications. I mapped something like this a few years ago to identify undue influence in municipality.