<|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:"Gender Bias in Asylum Adjudications: Evidence for Leniency toward Token Women."
Abstract:"Gender is one of the most frequently studied variables in the literature on judicial decision-making. We add to this literature by hypothesizing that the impact of applicant gender is conditional on the gender balance in a judge's caseload. We expect that female applicants receive more favorable decisions from judges whose caseload skews strongly male. Analyzing over 40,000 rulings by the Austrian Asylum Court between 2008 and 2013, we find support for direct gender effects for applicants and judges (yet no significant interaction between the two). We also show that gender balance in the caseload is a strong moderator of applicant gender. Judges with predominantly male caseloads are strongly biased toward female applicants, whereas judges facing a gender-balanced set of applicants display hardly any gender bias at all. These findings tackle essential questions of democratic rule of law and human rights. They indicate that applicants' fundamental rights to a fair and equal trial may have been compromised. We discuss institutional remedies to reduce the potential for gender bias in Austrian asylum adjudication.."
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 = [];
Q3 = [];
Q4 = [0];
Q5 = [];
Q6 = [1].
Gender Bias in Asylum Adjudications: Evidence for Leniency toward Token Women
Gender is one of the most frequently studied variables in the literature on judicial decision-making. We add to this literature by hypothesizing that the impact of applicant gender is conditional on the gender balance in a judge's caseload. We expect that female applicants receive more favorable decisions from judges whose caseload skews strongly male. Analyzing over 40,000 rulings by the Austrian Asylum Court between 2008 and 2013, we find support for direct gender effects for applicants and judges (yet no significant interaction between the two). We also show that gender balance in the caseload is a strong moderator of applicant gender. Judges with predominantly male caseloads are strongly biased toward female applicants, whereas judges facing a gender-balanced set of applicants display hardly any gender bias at all. These findings tackle essential questions of democratic rule of law and human rights. They indicate that applicants' fundamental rights to a fair and equal trial may have been compromised. We discuss institutional remedies to reduce the potential for gender bias in Austrian asylum adjudication.