"Reportedly"? I thought the media was unreliable. Who reported that information? How do you know it is true? That is a big supposition.
What information is incorrect in the Census data and how do you know it is wrong?
Who is "my Queen"?
The media is hilarious...
- Thread starter TTQ64
- Start date
"Reportedly"? I thought the media was unreliable. Who reported that information? How do you know it is true? That is a big supposition.
What information is incorrect in the Census data and how do you know it is wrong?
Who is "my Queen"?
I didn't say it was "reliable" I used the word "reportedly" for a reason. I looked at at close to a dozen sources.
Start here:
Coverage errors in census enumerations are of two types: inclusion of people in the enumeration who should not have been included, and omission of people who should have been included. People mistakenly included in the census comprise two types. First, erroneous enumerations are those who should not have been included in the census because they were not residents of the United States on Census Day, such as babies born after Census Day, people who died before Census Day, temporary visitors, and fabricated people. Second, there are duplicates of correct enumerations, representing people who appear more than once in the list of census enumerations. Duplicates can be repeat enumerations of the same individual at the same address, either as a result of the multiple opportunities for being enumerated in the census, or from an address being represented in more than one way on the Census Bureau’s Master Address File (MAF). Duplicates can also result from the inclusion of an individual at two different residences, possibly both of which are part-time residences. (We do not consider whole-person imputations or whole-household imputations, used either when an enumeration has less than two characteristics or when the number of persons living at a housing unit is estimated, to be a source of either duplications or erroneous enumerations, but rather to be a means for producing counts that are as accurate as possible when aggregated to various levels of geography.)
People who were not included in the list of census enumerations but should have been are census omissions. Omissions can result from a missed address on the MAF, a missed housing unit in a multiunit residence in which other residences were enumerated, a missed individual in a household with other enumerated people, and people with no residence.
In addition to omissions, erroneous enumerations, and duplications, enumerations in the wrong location can also affect the accuracy of census counts. A count in the wrong location can result from (1) a misunderstanding of the census residence rules and the resulting reporting of someone in the wrong residence—for example, having an enumerator assign someone to the wrong choice from among several part-time residences, and (2) placing an address in the wrong census geographic location (called a geocoding error).
Furthermore, demographic errors, which occur when a person’s demographic characteristics are incorrectly reported or assigned and which can also result from an improper imputation of an individual’s demographic characteristics, can add error to census counts. For example, if someone’s age is misreported on the census form, this adds one tally in error to the count for one age group and subtracts one tally in error for another. However, this does not impact census counts that are not disaggregated by age group.
Erroneous enumerations and omissions contribute to errors in census counts for any geographic aggregate that includes the addresses of the persons involved with those errors. Whether or not errors in geographic or demographic characteristics result in errors in census counts depends on the level of demographic and geographic aggregation for which the census counts are used. The more detailed the geographic and demographic domain of interest, the greater the chance that errors in geographic and demographic detail will affect the quality of the associated counts. For example, placing a person in the wrong census tract but in the right county is not an error for census applications except when one uses census counts below the county level. However, placing someone in the wrong state affects most uses of census counts. Similarly, attributing someone to the wrong age group does not affect overall population counts at any level of geographic aggregation, but it will result in an error for counts by age group.
As touched on above, errors in census counts can result from missing information and the resulting use of imputation for item and unit nonresponse. For example, missing information on the total number of residents in a housing unit can result in imputation of this number, which can add to errors in census counts of the total population for areas containing that housing unit. As described in National Research Council (2004b: 128, Box 4.2) the 2000 census used item imputation, whole-person imputation, and four types of whole-household imputation to complete responses with missing information. The procedure used depended on which persons in a household were and were not census data-defined. (A person’s enumeration was data-defined if there were at least two basic data items reported, including name as an item). Item imputation was used when all members of a household were data-defined, but some basic items were not reported. Whole person imputation was used when at least one member of a household was data-defined, but at least one other member was not. (Therefore, any enumeration that is not data-defined results in a whole-person imputation.) For the members of a household who were not data-defined, all basic information was imputed, using characteristics of other household members. Finally, four types of whole-household imputation were used, depending on whether the number of residents was known, the number of residents was not known but the occupancy status was known, the occupancy status was not known but it was known that the address was a housing unit, and finally it was not known whether the address was a housing unit.
As discussed in Chapter 3, the result of an individual imputed enumeration should not be considered to be correct or incorrect, but rather, one should assess an imputation algorithm based on its contributions to the bias and variance of estimated counts for various geographic areas and demographic groups. Therefore, whole-person and whole-household imputations can increase the errors in census counts for any demographic and geographic domains containing the people in question. Furthermore, imputation of characteristics can impact the quality of the counts for the associated demographic groups.
Two approaches have been taken to date to assess the overall (coverage) quality of census counts. One view is that census quality should be measured, separately by domain, by estimating the percentage net coverage error for each domain, for example, for each state. A second view is that census quality for a given domain should be measured instead by the percentage of census error—by census error we mean the totality of omissions, erroneous enumerations, duplications, and errors in the wrong location, with all errors receiving the same weight. This statistic is often referred to as the rate of gross census error.
As explained in Chapter 1, the Census Bureau is moving away from the view that the primary measure of census quality should be net error, because net error ignores errors of omission and erroneous enumeration and duplication that balance out for some levels of aggregation. On one hand, such errors that cancel at some level might contribute to error in measures at a lower level at which they do not cancel. On the other hand, the rate of gross census error is also deficient as a summary measure, in that many enumerations in the wrong location will affect only the more detailed aggregates. This argues for separate treatment of errors in the wrong location. Furthermore, since component coverage errors have partially distinct causes, it is important to separate the summaries of these various components so that their magnitudes can be assessed individually, rather than trying to place them into a single error measure. These last two points argue for separate measures of the four components of census coverage error: duplicates, erroneous enumerations, omissions, and enumerations in the wrong location. In addition, for errors in the wrong location, rather than a percentage error measure, which would be appropriate for omissions, erroneous enumerations, and duplications, a summary assessment would require a representation of the distribution of the size of the geographic errors to assess which applications of the counts are likely to be affected by various magnitudes of errors.
Measures of component census error consistent with the above considerations will provide useful information in support of a feedback loop for identifying alternative census processes that are preferred to current ones. However, this does not mean that the Census Bureau should not also continue to provide estimates of net coverage error. Such measures still have importance since (1) they can be compared with previously published estimates for historical comparisons of census quality, (2) as discussed in Chapter 3, net error measures are needed for estimating census omissions, and (3) users find net error measures useful for evaluating the utility of estimates for some applications.
https://www.nap.edu/read/11941/chapter/4#25
Happy reading!
None of which negates the fact that they'd already ruled that the ads were compliant. Presumably they know their own policies better than the Speaker of the House.
She reportedly told them the ads should be taken down, and they obeyed, just like you obey your Queen.
Althea
Althea told me...........
Yea...if horse races took 3 years!
I listen every day
They will, now that the clowns are off the stage.
I'm hearing Don Henley in my head
Or 'trump cannot possibly beat Hillary.
christiefan915
Catalyst
None of which negates the fact that they'd already ruled that the ads were compliant. Presumably they know their own policies better than the Speaker of the House.
She reportedly told them the ads should be taken down, and they obeyed, just like you obey your Queen.
"Reportedly."
You keep saying "they ruled that the ads were compliant", "they" meaning Facebook execs? The owners of the company can make any rules they want and if people don't like it, they can stop using FB. Here is what FB says about political ads, my darling duke.
Ads about social issues, elections or politics are:
- Made by, on behalf of, or about a current or former candidate for public office, a political figure, a political party or advocates for the outcome of an election to public office; or
- About any election, referendum, or ballot initiative, including "go out and vote" or election campaigns; or
- About social issues in any place where the ad is being placed; or
- Regulated as political advertising.
Ads targeting the US that portray voting or census participation as useless or meaningless and/or advise users not to vote or participate in a census aren't allowed.
Ads can be placed in most formats except dynamic ads and boosted continuous live video. Currently, these ads can't run on WhatsApp, Messenger and Audience Network.
All ads will be added to the Ad Library, even if the advertiser who created them hasn’t completed the ad authorization process.
Our measures are frequently reviewed and implemented. We suggest that you routinely check here for latest information.
Yes, reportedly, dear Duchess.
Google "Facebook Pelosi Trump ads" and start reading.
Are you admitting that Facebook changed their rules to comply with nattering Nancy's request?
Althea
Althea told me...........
There's still a Dem primary
Althea
Althea told me...........
You really believe everyone is getting free college/healthcare?
Althea
Althea told me...........
Nah. They're just smart enough to know that Sanders will cost Dems 40 states. And they know that there is no free lunch.
In other words, somebody said it was true but you have no clue whether it was because a dozen sources says it was "reported."
That is like polls. Somebody reports how they voted (or will vote) but we don't know if they are telling the truth. However, we assume they were truthful when the poll results are very close to the election outcome (2016).
Althea
Althea told me...........
I was thinking the same thing
Althea
Althea told me...........
The media loves any trump election
You don't get to change what I said in an attempt to make a point.
christiefan915
Catalyst
I googled, and the articles were very informative. Most used words like "misleading", "deceptive", and "misinformation." Thank you for pointing me in this direction.
Facebook Removes Misleading Trump Census ADS - The social media company has had a permissive policy about truthfulness in political content. But it drew the line on interfering with the national census.
Facebook takes down deceptive Trump campaign ads — after first allowing them -The ads were misleading about the U.S. census, the social media platform said.
Facebook removes Trump campaign ads that look like Census forms hours after drawing criticism
Facebook decides to take down Trump 2020 campaign's 'census' ads - Facebook Inc on Thursday removed ads by President Donald Trump’s re-election campaign that asked users to fill out an “Official 2020 Congressional District Census” because the ads violate the company’s policy against misinformation on the government’s census.
Facebook Removes Misleading Trump Campaign Census Ads After Pelosi Rebuke
You said you did not know if it was reliable but only reported (by some unknown person). My post did not change the meaning of your statement.
The writers of some of the articles used words like "misleading", "deceptive", and "misinformation", and you stopped reading because your confirmation bias was sated, right?
Which part is not consistent with your post?
Somebody said it was true
You have no clue whether it was (true)
A dozen sources (you looked at) claim it was "reported"
The dozen sources may all all got their report from the same source.
What if I told you that Big Tech could have been responsible for President Trump’s impeachment?
Big Tech can shift up to 15 million votes in November, according to Dr. Robert Epstein, a DEMOCRAT-favoring liberal who is the senior research psychologist at the American Institute for Behavioral Research and Technology
Note here that over the last eight elections and 32 years, no president has won by more than 9.5 million votes. Shifting 15 million is easily enough to turn most any modern election.
Dr. Epstein said, “Big Tech companies now have unprecedented power to sway elections. In President Eisenhower’s famous 1961 farewell address, he warned not only about the rise of a military-industrial complex. He also warned about the rise of a ‘technological elite’ who could someday control our country without us knowing.”
“That day has come,” he laments.
There are reportedly many people who often make emotion-based voting decisions. They supposedly have no firm party allegiance and choose who they feel is the most likable candidate. So, if you could alter their perception, you ,ight alter their vote.
This is what big Tech can do.
By exposing voters to just the right news at just the right time, they could manipulate opinion at the crucial moment. This is nothing new.
Conservatives used to complain (pre-Internet) about how the mainstream media — which then had a virtual monopoly over information — shaped public opinion.
The difference now is that with Big Tech collecting information on hundreds of millions of users, it can devise algorithms that could support manipulation efforts. It also might better effect an illusion of impartiality.
Google just delivers what you search for in random order, right?
By inserting negative search suggestions under the name of a candidate, search engines like Google could shift the opinions of some voters by up to 43.4 percent, according to recent research at the American Institute for Behavioral Research and Technology.
The lead author of the study, the same Dr. Epstein mentioned previously, has reportedly conducted extensive research into what he calls the Search Engine Manipulation Effect (SEME). Dr. Epstein claims that if the whole of Big Tech favors the same candidate, it could shift up to 15 million votes in November. It’s why Epstein wrote last month that "Trump can’t win no matter which weak candidate the DEMOCRATS ultimately nominate.”
https://tinyurl.com/vkte9up
This part.
If you don't quote me accurately, using an equivocation as a linguistic trick to assign a different meaning to my statement is disingenuous.