Category: Knowledge translation

Thinking systems and collaboration in organizational use of ICT to achieve: accountability, governance and multidisciplinarity

ksenia cheinman‘s analysis of Information Communication Technology (ICT) content in organizations and government in the context of efforts towards an innovation, points to the need for a cooperative whole system approach. 

She provides useful resources on how to improve our approaches to knowledge/content sharing, no matter how basic the task. 

For most health and social involved organizations the resource capacity to manage such an approach dissuades bothering to read these ideas.  It is worth the time though if we are seeking accountability, governance and multidisciplinarity, the title of Cheinman’s article. 

… Innovation in the government can often seem like a symptom of wanting to prove that we are not years behind the private sector, an internal competition or a way to strategically launch one’s career. It is a means to the wrong ends. It operates under the guise of genuine service improvement, but if you look closely and more importantly broadly, in a sweeping gesture, across the whole organization ecosystem, more often than not every individual innovation breaks something else along the way. In fact, sometimes it creates irreparable large-scale damage and it spreads and propagates the same mentality across the organization, creating more of the same.

Gerry McGovern describes this production-first mindset very accurately:

Everyone wants to produce. Nobody wants to service and maintain. If you’re a new manager you must do something new. You must initiate new projects. You must produce. You must produce. […]

In 99 out of 100 conversations I have about digital, management only cares about volume. More. More. More. New. New. New. Innovative. Innovative. Innovative. It is so incredibly rare to find a manager who will invest time and money in helping people find stuff more easily. And, once a customer has found something, helping them understand it more easily. …

See the article herehttps://medium.com/@altspaces/digital-content-needs-accountability-governance-and-multidisciplinarity-48212ba03e2a

A guide to Politics and Coalitions in the dance of neutrality in —contested policy making activities

Karin Ingold’s post explains the role of scientific knowledge brokering in coalitions  in Integration and Implementation Insights https://i2insights.org/     In Ottawa, we have had various examples of this, be it the  Alliance to End Homelessness or  harm reduction networks.  I find it useful to reflect on Ingold’s point that suggests that the loss of neutrality in Adversarial advocacy results in, ” no possibility for knowledge brokerage exists.” and need to become “non neutral actors.”

What roles can science and scientific experts adopt in policymaking? One way of examining this is through the Advocacy Coalition Framework (Sabatier and Jenkins-Smith 1993). This framework highlights that policymaking and the negotiations regarding a political issue—such as reform of the health system, or the introduction of an energy tax on fossil fuels—is dominated by advocacy coalitions in opposition. Advocacy coalitions are groups of actors sharing the same opinion about how a policy should be designed and implemented. Each coalition has its own beliefs and ideologies and each wants to see its preferences translated into policies.

via When are scientists neutral experts or strategic policy makers?

Some tools to help us think about implementing evidence in our practice

Health Evidence www.healthevidence.org shares tools that guide practice evidence, developed in collaboration with local public health organizations.  While targeted at public health some of the tools provide useful approaches for emerging front line projects.

File:Garden tools.jpg

photo by: SpitfireTally-ho! / Spitfire at en.wikipedia

Looking for tools to help you find and use research evidence? Use the Health Evidence™ practice tools to help you work through the evidence-informed decision making process; search for evidence, track your search, and share lessons learned with your public health organization.

Example of tools:

See the current tools at their site herehttp://www.healthevidence.org/practice-tools.aspx

Architecture to keep track of the big picture of health learning and the ensuing interventions

From the journal of Implementation Science, https://implementationscience.biomedcentral.com/articles/10.1186/s13012-017-0607-7

…In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution.

Intersectionality explained

This paper shared as one of the resources was found by Vicky Ward https://kmbresearcher.wordpress.com/, who was at the Canadian Knowledge Mobilization Forum, http://www.knowledgemobilization.net/event/2017-canadian-knowledge-mobilization-forum/

 

PUT SIMPLY: According to an intersectionality perspective, inequities are never the result of single, distinct factors. Rather, they are the outcome of intersections of different social locations, power relations and experiences.

paper by  Olena Hankivsky, PhD of https://www.sfu.ca/iirp/ 

see the paper here: https://www.sfu.ca/iirp/documents/resources/101_Final.pdf

Charles Jennings shares his thoughts on “the myth of knowledge transfer”

 Spotted by Stephen Downes http://www.downes.ca/,  Charles Jennings shares his thoughts on “the myth of knowledge transfer”

spaced_practice

During a meeting at Cambridge University around 30 years ago I was thoroughly chastised by a Cambridge academic.

I’d used the phrase ‘learning delivery’ when describing computer-supported collaborative learning (CSCL) approaches. CSCL was one of the hot pedagogical approaches of the day – when network-based learning was in its relative infancy.

“Charles, my dear fellow”, said the Cambridge man, “we may deliver milk, but learning is something that is acquired, never delivered”.

Of course he was right. I’d been sloppy with language. What I’d meant by ‘learning delivery’ was ‘providing the resources and environments that help learning and, by inference, improved performance, to occur’. Learning takes place in our heads. We alone make it happen.

I guess the phrase I’d used was a shorthand. However, it was the last time I ever used it. It conveyed an inaccurate message.

see the article herehttp://charles-jennings.blogspot.ca/2017/05/the-knowledge-and-learning-transfer.html


… Exposure to other organisations’ experiences can also be very useful for our own organisation’s learning and development, but no two organisations are exactly the same. If we package up the acquired data, information and practices in one organisation it’s extremely unlikely that they can be simply unpacked and used as-is with the same effect in another, no matter how closely aligned the organisations might be. The ‘knowledge transfer’ model doesn’t even work between organisations in industries with relatively standardised process . What works for Mercedes is unlikely to work for Ford without quite a bit of thought and customisation.  …

If you had to classify every shirt as a single colour, what information would you lose about each shirt?

A 10 minute talk with Catherine D’Ignazio on http://www.cbc.ca/radio/spark, worth a listen,— in order to co-construct Data collection, to represent the limitations of data, being willing to visualize what is NOT THERE

 If you had to classify every shirt as a single colour, what information would you lose about each shirt?

Picture by (flickr CC/Ewan Munro)

We live in an era of unequalled amounts of data. The Big Data age. And the sheer volume of it can be overwhelming. But no worries, you can look at a data visualization, and it will clear it all up. There’s a graph, or a chart or an infographic! Each an objective distillation of reality, right there in pictures. Only, what if those visualizations don’t tell the whole truth?

Catherine D’Ignazio is an Assistant Professor of Data Visualization and Civic Media in the Journalism Department at Emerson College in Boston. She thinks that we tend to accept data visualizations as facts because they seem to present an expert and neutral point of view.

But Catherine says that the perspectives of groups like women, minorities and others can often be excluded from what we consider objective data about the world around us. Which is why, earlier this year when this episode first aired, she posed the question, what would feminist data visualization look like?

The Interview is here: http://www.cbc.ca/radio/spark/307-snitching-stealing-exclusions-and-more-1.3414341/who-do-data-visualizations-leave-out-1.3414350?utm_content=buffere6850&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer