Alternative to Private Surveys

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Revision as of 20:21, 8 June 2025 by Jonellepetermunoz (talk | contribs) (Alternative to Surveys)
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Surveys are important in a democratic country to capture public sentiments and shape national policy.

However, because of the huge difference between the actual May 2025 results and pre-election surveys, many Filipinos no longer trust survey results. Anyone can read a lot of negative Facebook comments every time there is a new survey from these private survey firms.

I have a suggestion as a private citizen:

1. Rappler can conduct its own survey with similar questions from private survey firms.

2. Rappler will not release its survey result if there are not at least 1,800 respondents, and if there is no minimum number of respondents per region or city, and if different demographics are not properly represented.

3. The survey will only ask the following demographics:

a. Region, Province, City, and Barangay

b. Age range

c. Income range

d. Survey questions

4. NO name, phone, and email address for privacy purposes, just a valid Facebook account, like a Google Form clicked from FB. This will reduce spammers.

5. The form must have the ability to capture IP address at the backend to also reduce duplicate surveys from the same person.

6. The raw data and the survey result shall be publicized by Rappler. There is no evasion of privacy since there is no name, phone, and email address.

7. Any data scientist can use the raw data to create the survey result, since the raw data is open and public.

I believe that there are many data scientists in the world and in the Philippines who can make meaningful predictions and analyses. However, what they lack is the raw data to analyze.

If we could have done the above in the last election, and it happened that at least one data scientist could predict the result based on raw data, then that data scientist would have more credibility than the multimillion-commission surveys of the private firms.

The reputation of the data scientist will be at stake in analyzing each raw data, and its reputation will be as good as its last prediction.

Any data scientist can also publicly explain how he cleans the data, analyzes the data, makes the prediction, and basis for the margin of error.

At least the process and prediction is open and transparent. Let's just help data scientists to have raw data to analyze every survey.