Who cares about SF's (black and brown) prisoners? Part 2


Eileen Hirst of the San Francisco County Sheriff’s Office just sent me statistics that prove that the majority of folks sitting in our county jails are black men awaiting trial -- statistics that underscore the extent to which the “let’s not rebuild the prison” debate really is racially tinged:

“On any given day, we have about 2000 to 2100 people in custody,” Hirst said, noting that the two jails at the center of the debate only house male prisoners.

The biggest group in custody, Hirst said, are African American (58 percent). Next come Caucasians (18 percent), Latinos/Hispanics (15 percent), Asians (4 percent) and others (4 percent).

The overwhelming majority are male (87 percent).

And the vast majority (80 percent) are simply awaiting trial.
”Only 20 percent of the jail population is sentenced,” Hirst said.

So, does this mean that the nine supervisors who voted this week for a $412 million seismic safety bond that won’t upgrade these jails are racist?

No, but it does suggest that they believe that voters won’t support a bond that uses money to help build safe facilities to house black men in custody. Instead, the $412 million bond they voted to place on the June ballot will be used to build a new police command center, and retrofit firehouses and secure their water supply.

“No one is saying that we’re not going to rebuild the jails, but they are going to do the project in phases, and this bond represents the first phase,” Hirst said.

She noted that two previous attempts to pass bonds to rebuild prisons failed to get the required two-thirds of voter approval.

(In 1992, 57 percent of voters approved a $158  million general obligation bond, ten percent short of the needed 67 percent. Two years later, in 1994, only 54 percent of voters approved a similar bond, only know the same project’s costs had expanded to $195 million.)

‘And at that point we were under a federal court order to rebuild the jails,” Hirst said. She recalled how hot water had to be pumped in from a flatbed truck parked on the front lawn in front of those facilities that lay just two football fields away from the San Andreas fault, and that they have since been rebuilt.

Hirst said community groups went out with huge photos of those poor conditions, but the public still didn’t vote to support the bond, and the jails eventually got  rebuilt through a “certificate of participation” financing mechanism that Monique Moyer (who was then mayor Willie Brown’s director of public finance) came up with.

“So. I don’t think we are not going to rebuild," Hirst said. "But we do operate in a landscape of competing priorities.”


Our author has reached the prayer can cure disease stage of logical thinking.

Next blog to be about earthquakes caused by global warming.


Correlation does not equal causation
From RationalWiki
Jump to: navigation, search

Correlation does not equal causation is a quip that expresses the logical fallacy involved in the dichotomy between events that merely have a tendency to occur together, versus sequences of events that are actually causal. The form of fallacy that it addresses is known as post hoc, ergo propter hoc or "affirming the consequent".

Simple example

Two events can consistently correlate with each other but not have any causal relationship. An example is the relationship between reading ability and shoe size across the whole population of the United States. If someone performed such a survey they would find that the larger shoe sizes correlate with better reading ability, but this does not mean large feet cause good reading skills. Instead it is caused by the fact that young children have small feet and have not yet (or only recently) been taught to read.

This example also brings up the existence and problem of what are known as "confounding variables". A confounding variable is something that is not under direct control in the correlation experiment. - in this case, age, as it influences both reading age and shoe size quite directly. A confounding variable can be what the actual cause of a correlation is, hence any studies must take these into account and find ways of dealing with them. The most common method to control confounding variables is with controlled studies. In these studies, the differences between the observations and the control group are minimised as best as possible so that one can be more confident that a correlation is valid. This is extremely important in compensating for the placebo effect in medical trials, but it is also important in other branches of science, for example, in chemistry where reactions are repeated in different solvents to determine their effect on a reaction.
[edit] In science

In science, correlation studies are often used to test for the existence of interesting patterns, but they are never used exclusively to claim a cause. In order to make a causal claim you must run an experiment or series of experiments and further studies using the scientific method - i.e., test to see if it really is a cause by altering parameters and performing more experiments, making predictions and testing them. This is in order to validate that one event is indeed directly influencing the other and is the reason behind the detected correlation. Many woo and pseudoscience pushers conflate correlation with causation in order to make a claim of validity but forget to attempt the later scientific steps of compensating for confounding variables and thoroughly testing the causal relationship. For example, if someone gets a common cold, and takes vitamin C, their cold will go away in 5-7 days. The claim is then made that the vitamin C caused the cold to go away. However, the cold would have gone away anyway, whether or not the vitamin C was taken, and so the validity claim is false. The placebo effect is another correlation with "treatment" that quacks use to create false validity.

Correlations seem to tap into a deep part of human psychology. As pattern recognition machines, we are hyper-responsive to any potential signal in our environment. People will often take two completely unrelated events and decide that they must cause each other because they seem to correlate. Someone may decide that when they wear a given shirt they have good luck, this is often combined with a powerful confirmation bias to create magical thinking.

Posted by glen matlock on Feb. 28, 2010 @ 8:18 am

Where can I find part 1?


Posted by Dom on Mar. 06, 2010 @ 7:15 am