Extensive Detailed Tweet Topic Labeling for Training Data BY HAND

I'm in need of a native-English speaker freelancer to assist with labeling text posts by topic (to aid in machine learning research). Must be familiar with US politics, US current events, and US culture to be able to distinguish subtley different topics.

Key Requirements:
- Labeling up to 5,000 tweets as to whether they are about different topics from a list. Must use good human judgment.
- Must be labeled by hand (no machine learning or AI) by a native English speaker very familiar with US culture -- ideally having lived in the US for more than 1 year, within the past 3 years.

Task:
-Open the attached spreadsheet
-Read the FULL TEXT of each tweet. Also read the brand handle and sector for reference. Make sure to pay attention to any hashtags included.
-You do not need to open any URLs. Make your judgment based only on the text.
-If the tweet is about sustainability, enter "1" in column E. If it is not about sustainability, enter "0" in column E.
-Note that "sustainability" is a broad topic -- it is often a judgment call as to whether a given text is about it. Use your best judgment.
-If you are very unsure about whether the tweet is about one of the topics, or if the tweet it not in English, enter your best guess into column E, and enter a 1 into column F.

Notes:
-I cannot provide the spreadsheet in advance. But we can do small milestones if you prefer once we set the project.