<|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:"I'm happy to own my implicit biases': Public encounters with the implicit association test."
Abstract:"The implicit association test (IAT) and concept of implicit bias have significantly influenced the scientific, institutional, and public discourse on racial prejudice. In spite of this, there has been little investigation of how ordinary people make sense of the IAT and the bias it claims to measure. This article examines the public understanding of this research through a discourse analysis of reactions to the IAT and implicit bias in the news media. It demonstrates the ways in which readers interpreted, related to, and negotiated the claims of IAT science in relation to socially shared and historically embedded concerns and identities. IAT science was discredited in accounts that evoked discourses about the marginality of academic preoccupations, and helped to position test-takers as targets of an oppressive political correctness and psychologists as liberally biased. Alternatively, the IAT was understood to have revealed widely and deeply held biases towards racialized others, eliciting accounts that took the form of psychomoral confessionals. Such admissions of bias helped to constitute moral identities for readers that were firmly positioned against racial bias. Our findings are discussed in terms of their implications for using the IAT in prejudice reduction interventions, and communicating to the public about implicit bias.."
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:
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I'm happy to own my implicit biases': Public encounters with the implicit association test
The implicit association test (IAT) and concept of implicit bias have significantly influenced the scientific, institutional, and public discourse on racial prejudice. In spite of this, there has been little investigation of how ordinary people make sense of the IAT and the bias it claims to measure. This article examines the public understanding of this research through a discourse analysis of reactions to the IAT and implicit bias in the news media. It demonstrates the ways in which readers interpreted, related to, and negotiated the claims of IAT science in relation to socially shared and historically embedded concerns and identities. IAT science was discredited in accounts that evoked discourses about the marginality of academic preoccupations, and helped to position test-takers as targets of an oppressive political correctness and psychologists as liberally biased. Alternatively, the IAT was understood to have revealed widely and deeply held biases towards racialized others, eliciting accounts that took the form of psychomoral confessionals. Such admissions of bias helped to constitute moral identities for readers that were firmly positioned against racial bias. Our findings are discussed in terms of their implications for using the IAT in prejudice reduction interventions, and communicating to the public about implicit bias.