The Educators’ Datafied Present and Future: Complexity as an Approach to Developing Educators' Data Literacies

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics’ data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the need to develop academics’ data literacy to embrace fair practices, this literature is often also rooted in a technical or data-driven perspective. In this paper, the authors summarize an empirical study based on 137 articles using the terms “data literacy,” “teachers,” and “faculty development,” spanning from 2014 and 2019. The findings point out that out of the total, 78 papers reviewed took an instrumental, data science-focused perspective on data literacy, were the technical abilities like extracting data and interpreting or reporting appropriately (authors, in press). Data safety and effective data management perspectives accounted for another 35 of the 137 articles. Only seven took up data literacy from a critical perspective, while only five looked at the pedagogical practice. These preliminary findings require awareness and discussion on the light of appropriate faculty development approaches and activities. We introduce some recommendations aimed at understanding data as a complex emerging phenomenon in our societies, which requires building the literacies to face their negative effects like data surveillance and algorithmic biases, but also, to uncover its emancipatory power.

Decentralising Data Collection and Centralising Information in the People’s Republic of China: Decentralise, Manage, and Service Reforms

Xi Jinping’s ascent to power as Chairman of the Chinese Communist Party (CCP) was accompanied by changes in national governance strategies in the People’s Republic of China (PRC) that have progressively incorporated the use of big data. Shortly after, in May 2015, the Chinese State Council released a set of policy reforms under the abbreviation fang guan fu 放管服 (decentralise, manage, and service). These reforms promoted big data led (1) market regulation, (2) supervision and management systems, and (3) service provision processes. By applying a case study analytical approach, this paper explores how advancements in big data contributed to these reforms aimed at centralising information in China. Combining the joint knowledge of surveillance and China studies scholarship, this paper offers evidence of big data surveillance streamlining China’s fragmented intergovernmental policy system. We build on David Murakami Wood’s 2017 outline of a political theory of surveillance and argue that decentralisation of data collection points and centralisation of both bureaucratic and public access to information are key components of the Party-state’s regulatory governance strategy incorporating the use of big data and comprehensive surveillance. Our findings have implications for future analyses of the relationship between political organisations and surveillance within other nation-state contexts, particularly in situations where Chinese technologies and systems are being adopted and adapted.

Modeling the age distribution of retinoblastomas

In this work, based on real data on the size of the eyeball (in a fetus, in a child, and in young people under 20), we constructed a model function of the growth of the retinal cell tissue. We used this function to construct a theoretical age distribution of retinoblastomas. We constructed theoretical age distributions for four different models of retinoblastoma: a complex mutational model, a third mutational model, a model with a sequence of key events, and a model of a single oncogenic event with two different latencies (hereditary and non-hereditary retinoblastoma). We compared the theoretical age distribution of retinoblastomas with the real age distribution based on SEER data (Surveillance Epidemiology and End Results; program of the American National Cancer Institute). In total, we examined 843 cases in women and 908 cases in men. For all models (separately for women and men), we obtained estimates of the following cancer parameters: the specific frequency of key events (events that trigger cancer); the duration of the latency period of cancer; the number of key events required for cancer to occur. For the composite age distributions, we calculated the theoretical mean age at diagnosis for hereditary and non-hereditary retinoblastomas. The best approximation accuracy (for male and female forms of retinoblastoma) is shown by a model with a sequence of key events.

Big Data Surveillance

On October 21, 2021, Dr. Valerie Steeves presented Big Data Surveillance: Privacy and Trust Implications at the October 2021 CASIS Digital Roundtable event. This presentation was followed by a question and answer period, where CASIS Executives and attendees were given the opportunity to discuss the presentation with Dr. Steeves. The discussion topics included building an understanding of data surveillance for young people and safeguarding their privacy through building trusting relations.

An Overview of COVID-19 Vaccine Safety and Post-marketing Surveillance Systems

The need for the safety monitoring of the COVID-19 vaccine is unprecedented. It is an ongoing process starting from different phases of clinical trials and continued to post-marketing to tackle the emergency used authorized COVID-19 vaccines across the world. Rapid detection, exchange, prioritization, and assessment of safety signals based on available real-world data, surveillance of Adverse events following immunization (AEFI), and adverse event of special interest (AESI) by studying the observed/expected cases. Enhanced collaboration, and availability of resources, tools, and methods will add to the lessons learned from previous experiences.

Intelligent Plunger Lift: Digital and Cost-Effective Solution to Unlock Gas Potential in a Large Tight Gas Field in China

The field is located in a large gas producing basin in China and has prominent characteristics such as thin formation thickness, low permeability and poor reservoir connectivity. Horizontal drilling associated with multistage hydraulic fracturing has proven to be an effective technique to produce the hydrocarbon in this field. As the gas wells matures, the production rate starts to decline due to the decreasing of the bottom hole pressure which will prompt a liquid loading issue. A trending gas production loss is up to 150 mmscf in a year due to liquid loading issue alone, which is equivalent to $1.8MM revenue loss. An analytical decline rate showed that the field is declining 3.4% to 4.6% monthly due to the descending of the casing pressure, superimposed with low backflow ratio after hydraulic fracturing, which create a technical and economic challenge to produce effectively. In addition, the location between well pads are remote and far apart. This creates HSE challenge for personnel to go to the well pads, especially during icy road in the winter. Solid soap stick had been tried as a deliquifications method, unfortunately the result is unsustainable without frequent injection. It is also very much relying on human intervention. Due to that, an alternative liquid lift loading system is introduced in the field. An intelligent plunger lift has been piloted in 12 wells in the field to reduce the liquid loading issue in mid 2021. Apart from the apparent advantages of plunger lift such as mitigation of liquid fallback, zero input energy and low operating/maintenance cost, this system is not desirable to fully close well at downstroke process which comes up with increment of gas production comparing to traditional plunger lift system. One of the major advantages is the real time production data surveillance to enable remote operations based on its intelligence flow control system and downhole sensor.

Digital Capitalism, Datafication, and Media Education

As digitization and datafication continue to extend into all areas of society, digital capitalism becomes equally ubiquitous and universal. Digital capitalism, and related phenomena such as data, surveillance or platform capitalism, operate on the basis of a comprehensive expropriation and exploitation of personal data profiles. It functionalizes life worlds and places of education to an unprecedented extent. This special issue is responding to the following questions: What position/s can media education in research and application take to respond to these developments? Which theories, concepts and methods help to formulate adequate analytical, critical and transformative answers?