User:Loraaljbour/sandbox

Data Universalism is a concept that shapes our interactions with others and how we view the world through a generalized approach in data collection and with no consideration to geographical borders and social contexts. Data are used in universal endeavours across social, political, and physical sciences unrestricted from its local source and people. Data is gathered and transformed into a mutual understanding of knowing the world which forms theories of knowledge. One of many feilds of critical data studies explores the geologies and histories of data by investigating data assemblages and trace data lineage which unfold data histories and geographies (p.36). This reveals intersections of data politics, praxes, and powers at play which challenges data universalism as a misguided concept (p.134).

Theoretical Framework
While data universalism assumes data is representative of all, it is unlocalized and Western epistemic. Data, as we know it, is mainly sampled in rich Western countries which are considered the leaders and voice of technological developments despite its application being widespread which ignores cultures, communities, and geographies. Essentially, as the data lifecycle is enlarging, there are processed small data that are grounded within the Big Data that is compiled and formed from heterogeneous sources extracted from mainstream places by which knowledge is extracted.

So far, research has not evidently shown the motives behind universalism as a practice due to a lack of controlled data. It is believed that democracy and universalism have a positive correlation, according to cultural psychologists, but there are no studies that show how universalism is shaped by peoples experiences and environments. A push toward datafication has been spurred by democratically advanced Western voices and diffused across fragile democracies in the Global South with no consideration to the geopolitical context and influence powers of the data landscape in countries outside the West. Presently, obscure information is found on the epistemology of universalism but, it has been argued that the lack of representative data is problematic for broad global analyses.

Criticism
Data Universilism has been critiqued by many scholars concerned about data privacy and data justice, claiming that it conceals cultural specifications and diversification. Datafication ought to be viewed in the lens of epistemic diversity, justice, thus obedient. So, we are encouraged to critically examine the impacts of datafication and how it came to be by reimagining people and place.

De-westernization
Stefania Milan and Emiliano Treré have contended datafication as a privileged practice carried by dominant Western democracies that fails to see the richness of worldviews and meanings of the South. As promoted by Global South and Indigenous scholars, data universalism mistakenly assumes data to be universal when it ought to be treated differently. If data is extracted without an ethics foundation grounded by attitude and method, the data becomes pervasive and incompetent. Moreover, shifting the attention on factors that influence data extraction from a techno-centric viewed that is concerned with the the human agency behind data to data methods that stimulate discussions on the reprecussions of datafication requires relocating agency that assumes ethics and responsibility. A push for bottom up data practices shifts the focus of datafication to data justice to encourage citizens of the South to participate in political agency and repel from a highly opressed and inequal datafication process. Negligence in abstracting knowledge from others through diversifying social and historical contexts, will result in bias sampling techniques and methods in data generation. This causes skewed data to generate leading to unequal datafication.

Also, an aggregate technique used for data processing misrepresents data in a way that shapes an aggregate value as representing an aggregated individual, this adheres to the bias factor in making the subject appear as a collective by reducing variance and limiting space of contributions (p.192). Using an aggreggate technique submits to universal normitivity which situates what is considered to be universally right as a practice that does not take resposnibility of the context of a specific situation nor the interpretation of norms which are also subject to contexual interpretations. While humans operate in unique cases where information can be incomplete, agency empowers us to assess the situation and make radical decisions in complex situations where information is obscure. So assuming universal normitivity will not only incapacitate ones ethical validity when making choses but my lead to questionable decisions.

Global South
Historical processes of global capitalism and colonialism has majorly impacted the supply of knowledge from Western modernity and subordinated knowledge from the Global South. Colonialism, in this perspective, is understood as data colonialism which pressurizes but also exploits datatafication on communities. Global South and Indigenous scholars claim that decolonial lens that transcends to a Eurocentric perspective, adds value to critical data studies by questioning the geopolitics of knowledge, the depth of knowledge regeneration, and the power constructions of past injustices. Notions of data politcs and data justice are more interested in giving a voice to the underprivelaged and acquiring decolonial practices rather than issues concerning the blueprints of the political and social contexts of liberal democraces and social orders. Still achieving decolonial critical data studies comes with a unique set of challenges that confronts the knwoledge we have produced and knwoing what we know about the world, that is at the centre of epistemology. The wave of Big Data revolution feeds on insights of the production of data, how knowledge is produced, and how it is conducted and governed while using new epistemologies to make sense of the world.