Quantitative Methods Flashcards
Big-data thesis (?;?)
Mayer-Schonberger 2013
Will allow us to create much more responsive policy
Research in an n=all world - knowing what not why is good enough
What are data (?;?)
Kitchin 2014
Not neutral or objective - framed technically, economically, ethically, temporally, spatially and philosophically
Don’t exist independently of the ideas/contexts/instruments used to generate, process and analyse them
Selection of total sum of all possible data available = inherently partial
Sociotechnical assemblage – frames what is possible, desirable and expected of data
Open data movement
Data as a public good - should be freely accessible
e.g. gov data
Geolocation and language on Twitter (?;?)
Graham et al 2014
Locational and linguistic metadata from tweets
User-entered profile locations differ from physical locations
Significant challenges to accurately determining language
Big data classification (?;?)
Kitchin and Lauriault 2015
Huge in volume
High in velocity - near real-time
Exhaustive - n=all
Critique of “data” (?;?)
Adams St Pierre 2013
Conventional qualitative inquiry sees data as brute; not a representation of something
Vs. Deleuze and Guattari - cannot have data because being is always already entangled = cannot be something called data which is separate; doesn’t assume subject/object binary = might not think the concept of data at all
Why combine quant and qual (?;?)
Greene et al 1989
Triangulation = convergence, corroboration, correspondence
Complementarity
Expansion
Mixing methods in natural resource management (?;?)
Nightingale 2003
Qual methods able to capture issues of power and oppression
Mixing methods = examine partiality of knowledge produced in different methodological contexts
Nepal forest change = aerial photograph is the dominant representation
- she used qual, ethnographic, techniques such as oral histories, participant observation and in-depth interviews
- also aerial photographs and quantitative vegetation inventories
= both ecological change and social-political complexities
GIS for narrative analysis (?;?)
Kwan and Ding 2008
‘geo-narrative’
GIS for analysis of narrative materials such as oral histories
Lives of Muslim women in Ohio after 9/11
Lived experience
Rich and vivid accounts
What kind of changes has 9/11 brought to their daily lives, and their perception of safety and risk in the urban environment
Critical Quantitative Methods (?;?)
Kwan and Schwanen 2009
Quant rev 50s and 60s - making geography a scientific pursuit
But quant can be critical –> address issues of social justice and inequality
Challenge regressive political agendas often supported by quantitative analysis
Emphasis on local context rather than global generalisations
Critical Demography (?;?)
Ellis 2009
Vital to highlight social injustice and oppression
It’s the political right who want to obscure numbers – they reveal inequalities which undermine support for cuts in social programs
^ e.g. California Proposition 54 - end race and ethnic data collection
Inferential statistics a vital tool for estimating numbers of marginalised groups who would otherwise be undercounted
It’s necessary info for effective resistance of oppression
Transport for London (?;?)
Marr 2015 in Forbes
Aim = how to meet the demand of growth in London by being most efficient
Oyster cards - bus and train data
Produce maps showing where people are travelling
Can understand load profiles = how crowded
Biodiversity data (?;?)
Bowker 2000
Large number of disciplines collect biodiversity data
The database is performative -shapes the world in its image
e.g. only save what we count; counts can be skewed
Need to historicise our datasets - they are ontologically diverse
STS can help
H1N1 (?;?)
Sparke and Anguelov 2012
Inequalities in risk management: Outbreaks Near Me app = rich could have alerts; poor countries struggle to provide disease surveillance
