<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"BIBB Establishment Panel on Training and Competence Development The longitudinal data set***."
Abstract:"The BIBB Establishment Panel on Qualification and Competence Deve-lopment is the second largest annual panel survey of firms in Germany. In this arti-cle, we present the harmonised longitudinal data set from the first wave in 2011 to the 2019 wave, comprising 32,135 observations from 15,918 firms. We present information on the sample, study design and data collection and describe the cha-racteristics of the survey. We explain the structure of the long data set designed for facilitating panel analyses. The data provides comprehensive information on firms' human resources management, particularly in respect of vocational education and training and continuing training. Since 2016, the survey has also followed techno-logical change and the training and employment of refugees. We present previous findings using the data, based on which we give an outline of the survey's potential for future research. The Research Data Centre at the Federal Institute for Vocatio-nal Education and Training provides and regularly updates the data set.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
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BIBB Establishment Panel on Training and Competence Development The longitudinal data set***
The BIBB Establishment Panel on Qualification and Competence Deve-lopment is the second largest annual panel survey of firms in Germany. In this arti-cle, we present the harmonised longitudinal data set from the first wave in 2011 to the 2019 wave, comprising 32,135 observations from 15,918 firms. We present information on the sample, study design and data collection and describe the cha-racteristics of the survey. We explain the structure of the long data set designed for facilitating panel analyses. The data provides comprehensive information on firms' human resources management, particularly in respect of vocational education and training and continuing training. Since 2016, the survey has also followed techno-logical change and the training and employment of refugees. We present previous findings using the data, based on which we give an outline of the survey's potential for future research. The Research Data Centre at the Federal Institute for Vocatio-nal Education and Training provides and regularly updates the data set.