<|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:"How helpful are social networks in finding a job along the economic cycle? Evidence from immigrants in France."
Abstract:"Around 50% of individuals obtain or hear about jobs through social networks. This hiring trend may become problematic when the labor market is tight and people need less social contacts to find a job. Using a one-period static model where network members may receive job offers directly from the firm or indirectly through employed members in the network we show that the share of new hires finding a job through social connections (ie network matching rate) decreases with the job finding rate. Using French data for the period 2003-2012, we test this prediction with immigrants, a population subgroup for whom networks play a major role in occupational decisions. We propose two network matching rate indicators, one based on direct recommendations and another one internalizing the positive externality on the employment probability induced by peers. We find a decreasing relationship between the network matching rate and the job finding rate. Social connections are less helpful for finding jobs during economic expansions.."
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: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [3];
Q3 = [];
Q4 = [0];
Q5 = [1];
Q6 = [1].
How helpful are social networks in finding a job along the economic cycle? Evidence from immigrants in France
Around 50% of individuals obtain or hear about jobs through social networks. This hiring trend may become problematic when the labor market is tight and people need less social contacts to find a job. Using a one-period static model where network members may receive job offers directly from the firm or indirectly through employed members in the network we show that the share of new hires finding a job through social connections (ie network matching rate) decreases with the job finding rate. Using French data for the period 2003-2012, we test this prediction with immigrants, a population subgroup for whom networks play a major role in occupational decisions. We propose two network matching rate indicators, one based on direct recommendations and another one internalizing the positive externality on the employment probability induced by peers. We find a decreasing relationship between the network matching rate and the job finding rate. Social connections are less helpful for finding jobs during economic expansions.