Questions about poll results
Next to Democratic Party presidential candidate Hillary Clinton, the biggest losers in the recent US presidential elections were the polling or survey companies.
Except for Los Angeles Times/University of Southern California, all national pollsters gave Clinton the lead over Republican Party presidential candidate Donald Trump.
In the last pre-election surveys, the probability of Clinton becoming the first US female president ranged from a conservative 71 percent to a high of 99 percent.
These optimistic projections were shared by major US television networks and newspapers. They discussed the figures as if the election was over except the counting of votes.
So confident was Clinton’s party of her win that the ceiling of the venue for its victory party was decorated with glass panels to symbolize the “breaking of the glass ceiling” or a woman finally assuming the highest office of the land.
As things turned out later, it was the pollsters’ ego, rather than the proverbial glass ceiling, that got broken as Trump beat Clinton and, to aggravate matters, won in the traditional bailiwicks of the Democratic Party.
The surprising turn of events put the pollsters on the hot seat. Given their much vaunted expertise, polling experience, sophisticated algorithms and army of analysts, how could they have been so wrong in their projections?
With the pollsters’ credibility on the line, questions have been raised about their “mathematical models, assumptions and survey methods.”
In the wake of this embarrassing event, an officer of the organization of US surveys or research companies said their members would soon meet to review the methodology and procedures used during the campaign to find out why their figures did not match the election results.
The situation that US-based polling companies has found themselves in invites attention to the organizations in our country that are similarly engaged in survey or data-gathering activities for political, economic, social and commercial purposes.
The local research companies are organized along the lines of US polling organizations in terms of, among others, criteria for the selection of respondents, wording of survey questions, harvesting of data and evaluation of responses.
Bear in mind that polling (or getting the public’s opinion on certain issues) is an American invention. It was started in 1935 by George Gallup who, in 1936, successfully predicted that Franklin Roosevelt would defeat Alfred Landon for the US presidency.
In recent years, poll surveys have become regular fixtures in our national elections. The publication of survey results has been criticized, however, for indirectly creating a bandwagon effect for candidates who are supposedly on the “winning list.”
Between elections, there are polls on the public’s perception on how well or how bad the country’s top government officials are performing their duties and responsibilities.
Retail-oriented companies, TV networks and advertising agencies rely on research companies in planning their sales campaigns and other revenue-related activities.
Whether or not these surveys, or any similar activity on other subjects, are credible and can be relied upon to guide future action is up for their readers or the parties who commissioned them to decide.
Outside of general statements about the way the poll was conducted or the number of respondents, there is really nothing else that the public can look at to determine whether the results are accurate or were skewed to serve the interests of whoever commissioned them.
Survey or research companies consider the raw data, methodology and algorithm they used to come up with the results as either confidential or proprietary and therefore not fit for public disclosure.
The US presidential elections poll fiasco is an eye-opener. It showed that polls are fallible and may not accurately reflect the information sought to be conveyed by their results.
A similar approach should be taken when we read so-called surveys or research findings on subjects that tend to influence our daily lives.
Caveat emptor (or let the buyer beware).
