Created: 2025-09-20 11:13:38 - Touched: 2025-12-24 14:59:07 - Status: Seed

Dalkir, K. (2023). Knowledge Management in Theory and Practice (4th ed.). MIT Press.

Chapter 1

Open questions

Are there concrete applications besides in decision making? If the goal of Concept Analysis is to generate consensus, why are we asking each organization to undertake it individually? Is the value of a piece of knowledge intrinsic, or is it defined by the impact it has on decision making? Are we going to talk about deprecation/destruction? Is KM worthwhile in non-competitive organizations? Do the people producing the knowledge have a right to it as individuals, and do KM professionals have a responsibility to protect the individual's rights to their own knowledge and their privacy? What ethical standards and values should we ascribe to?

My definitions

Data is cold hard facts, the numbers in the spreadsheet.

Information is analyzed data, conclusions drawn from that specific data.

Knowledge is the synthesis of information for the purposes of enjoyment, identification of opportunity, and decision making. Can be difficult to capture, structure, communicate.

Knowledge Management is the generation, identification, importation/exportation, documentation, organization, discoverabilitization, valuation, curation, deprecation/destruction, and optimization of knowledge for retrieval and use at point of use in a systematic way; achieved through tools, processes, and culture.

What

No one knows what KM is. Hundreds of definitions and conflicting/ambiguous terms. Each organization needs to define what it means by KM. Concept Analysis is a way to achieve that: generate or import many definitions of KM for analysis, and analyze them to produce a list of attributes. Each attribute gets one or more illustrative examples and illustrative non-examples. This can allow for easier delineation of underlying concepts, which can then be distilled into a working definition.

Why

KM is essential for organizations to capitalize on knowledge for the purposes of optimization and innovation. KM is important because of globalization, information overload within organizations, workforce mobility, technological advances, and the proliferation of disinformation. Share lessons learned, best practices, systematic approach to knowledge sharing and cultivation. Organizational knowledge largely goes home at the end of the day; with a more mobile workforce a departing employee takes a lot of value with them. Being able to capture that knowledge, both explicit (documented, easily shared) and tacit (hard to communicate, comes from experience), is important for holding on to that value. Not all tacit knowledge can be converted to explicit, so documentation isn't adequate to produce working KM.

How

Integrate at point of use, especially decision making. Try to convert tacit to explicit when possible to aid in dissemination (but beware misapplication and lossy encoding), incentivize experiential knowledge sharing. Integrate KM at the level of individual, group, organization, multi-organization/inter-organization, and society at large. Similar levels described in Information in Society.

First generation of KM focused on "containers" ie taking the knowledge that existed and documenting it for reuse and putting it into monolithic knowledge portals. Top-down and highly structured and rigid, no one used them because they were too generic.

Second generation of KM focused on people, figuring out who had the knowledge (esp tacit) to share/on a specific topic and the human cultural values involved; communities of practice, each team making their own wiki, bottom-up organization (lots of overlap, repeated work, unstandardized, hard to disseminate).

Third is focusing on the knowledge itself as a commodity. Metadata to increase discoverability, accessible at point of us, convince people it's good to use it/useful. Folksonomies instead of taxonomies. This has lead to a shift from optimization focus to more balanced with innovation.

Tools are good, processes are better, culture is best. Tech-focus can hinder tacit knowledge. Identifying the impact of KM on the organization is key to its implementation; you can't optimize what you don't measure. But beware of Goodhart's Law.

Intellobics Types of Knowledge

https://intellobics.com/kmwhiz/category/types-of-knowledge/

Tacit knowledge includes intuition and cultural knowledge, both of which are likely to contain biases. Tacit and explicit are transmitted in different ways (practice, mentoring vs reading an instruction manual). Tacit is asserted to be better for innovation and creativity. Can sometimes convert tacit to explicit via things like case studies and documenting of mentoring sessions, interviews with experts.

Reluctance to Share: Employees may be unwilling to share their tacit knowledge due to fear of losing their unique value or job security. Additionally, cultural and organizational barriers can discourage open knowledge sharing.

That seems like a reasonable concern. What do organizations do to alley that concern?

Geeks for Geeks: Knowledge Management

https://www.geeksforgeeks.org/business-studies/knowledge-management-meaning-concept-process-and-significance/

KM Process:

  1. Identify
  2. Capture
  3. Organize
  4. Share
  5. Transfer (this seems to be the same as sharing)
  6. Application
  7. Evaluation
  8. Maintenance

Assignment 1: Where is KM discussed online?

Blogs, Substack newsletters, YouTube channels, podcasts, linkedin, and other online media.

Corporate:

General

PKM

Class readings are another place to find domains to look at. "Knowledge management trends" or "knowledge management developments" search. Try searching on platforms rather than the whole internet.

I am frustrated by how little I'm finding about non-profits, academics, and especially Indigenous authors of these discussions.

Live Lecture 1

Nothing valuable happened here

KM explained in 10 minutes by productivity guy

Productivity Guy (Director). (2022, June 20). Knowledge Management-Explained in 10 Minutes [Video recording]. https://www.youtube.com/watch?v=-XPbfsl3WGo

Just an overview.

What is IK lecture recording

Non-western. Oral and experiential->holistic->dynamic and adaptive->contextual->back to oral. Doesn't have to be sterile and factual and "neutral." Not separated from natural surroundings. Relational and ecological, interdisciplinary, localized and land-based, collective and communal, spiritual and sacred. Intellectual property isn't the concept. Intergenerational (both towards the past and towards the future). Does not require validation by western science. Classifying indigenous science as "art". Indigenous "renaissance" since some of us are finally recognizing the value of these ways of knowing.

Two-Eyed Seeing

And other lessons learned within a co-learning journey of bringing together indigenous and mainstream knowledges and ways of knowing. Bartlett, C., Marshall, M., & Marshall, A. (2012). Two-Eyed Seeing and other lessons learned within a co-learning journey of bringing together indigenous and mainstream knowledges and ways of knowing. Journal of Environmental Studies and Sciences, 2(4), 331-340. https://doi.org/10.1007/s13412-012-0086-8

Key for success: We need each other and must engage in co-learning. Most profound: two-eyed seeing. Critical for long-term success: diverse advisory council. Albert of the Moose Clan coined the term two-eyed seeing Fall 2004.

Starting questions: What is two-eyed seeing, and what are its implications? Does it only apply to environmental/ecological concerns or does it extend beyond that? Is the goal to come to a single cohesive way of knowing, or to keep them individual and combine them only at the point of application? Does it only apply to education?

Environmental can apply to institution and community.

The introduction has an interesting way of introducing the authors and how they approach authorship of the paper. One hand writing for three people. Don't just make it up; include the actual voices of IK holders.

Possessing knowledge which is traditional or tribal, is a mirror image of your own spirituality. There is nothing that we cannot understand this way. Science can explain many things, but in the tribal world, there is another realm. Yet we value knowledge and we combine it with assistance we seek from the spirit world. One should not be afraid to seek assistance to develop a thought. In our world, you are a physical being and you are a spiritual being.

(Marshall, 2011)

To identify "lessons learned" requires lived experience in learning those lessons. Don't clobber people with your knowledge, but offer it freely to those willing to listen. Address absence of aboriginal students in science programs at universities by including IK ways of knowing side-by-side with western. Saw great success, but eventually that program fell apart. "Seeds germinate when the environment is right." Even those that don't finish the courses are still impacted by them in ways these three authors will never know.

Acknowledge that we need each other and must engage in a co-learning journey

If you can't or won't acknowledge that we need each other, then trying to co-learn will be a facade. It's us, together.

Be guided by Two-Eyed Seeing

One eye sees with the strength of IK/ways of knowing, and the other with the strengths of Western. Seeing with two eyes provides depth of perception. Outermost circle: physical properties of medicinal plant. One step in, personal connection. Then respect. And finally sacred nature (only to be understood in the native language of the people).

One might wish to talk about 4-eyed seeing or 10-eyed seeing. Mi'kmaw understandings are just one of many IKs.

Integrated IK must be authentic (and authenticated by people with that knowledge+responsibility). Appropriate sources for particular topics (IK is collective knowledge). Nourishment of the living relationships (because it's a community of knowledge). Lifelong learning journey (not just a 4-year degree).

View "science" in an inclusive way

Relates to socially relevant issues, transcends and integrates disciplinary paradigms, includes non-academic actors. Individual and collective, knowledge cannot exist without its historical and social context. Humanity as part of the natural world, not existing apart from and superior to it.

Do things (rather than "just talk") in a creative, grow forward way

Integrated two-eyed seeing concepts in Cape Breton, NS, and across Canada. Included in planning efforts and policy documents.

Become able to put our values and actions and knowledges in front of us, like an object, for examination and discussion

Use visuals

Like the 4 concentric circles. Text is good but it's not the only way to represent and communicate knowledge, and non-Western ways of knowing use non-text methods a lot more.

Weave back and forth between our worldviews

You shouldn't? can't? use both eyes on all problems all the time. Sometimes Western is the better approach, sometimes IK is. Weaving means using the right tool for the job, but doesn't appear to be discussed in practical terms (ie how do you choose which one is right? wouldn't someone embedded in Western knowledge think Western is the right tool always?)

Develop an advisory council

If you don't make seeking their input compulsory, universities won't. The political/institutional environment has a huge impact on the success or failure of these programs, and input from Elders being incorporated is a big step in the direction of success.

Concerns about the term two-eyed seeing

Focuses on separation and containment, while some IK focuses on collapsing the distance between human and animal. Eyes being a biological item and many sociologists resisting biology-based explanations for behavior.

Indigenous Corporate Training

What Does Indigenous Knowledge Mean? A Compilation of Attributes. (n.d.). Retrieved September 28, 2025, from https://www.ictinc.ca/blog/what-does-indigenous-knowledge-mean

Collection of terms and definitions.

Chapter 2: Processes

There are a number of major approaches to KM process. We're going to look in detail at 6 of them to see how they're similar and different. Dalkir is on one of them.

Is reuse a key component of all of these approaches? How do they produce innovation? How does globalization impact things?

Heisig did a comparison of 160 KM processes and found common categories for the steps. No one has a unified set of steps and definitions that everyone agrees on.

Meyer and Zack have stages that information goes through where it becomes more useful. Each stage requires work. "Knowledge" as an atomic thing that is embedded in a document. A single document can have multiple knowledge units in it. Knowledge is stored, but refining it increases its value.

Bukowitz and Williams. Differentiates KM from IM by including tacit knowledge. Get->use->learn->contribute. Use is primarily focused on innovation, in contrast to other approaches. Learn is about self-reflection but also organizational learning, but how does the organization learn until the individual contributes the knowledge? This book is poorly written. Assess->build/sustain->divest. Assess is something that groups and organizations do, sometimes using an assessment framework to identify value? What is build/sustain?? And divest apparently doesn't mean get rid of but to give it to some other area of the organization. Who wrote this crap? M&Z wasn't presented as a flow chart, but Dalkir asserts that B&W introduces "learn" and "divest" as new phases.

McElroy: feedback loops. Subjective and objective knowledge. When knowledge is used at the outcome is good, positive reinforcement. When knowledge is used and the outcome is bad, negative reinforcement of that knowledge within the KM system. Once has little/localized impact, repeated can cause whole organization to reject a piece of knowledge and learn something new instead. Operates on "claims", identified (gaps in) knowledge. Framing them as claims, to be validated or disproven, is helpful with disinformation. Evaluate the claim before integrating the knowledge. Proven, disproven, or proven/disproven in specific contexts. Aim for proven practice rather than best practice. Evaluation of claims is good.

Wiig: building->holding->pooling->applying. Collect knowledge from various sources (synthesis, analysis), store it in your brain or write it down etc, dump it into the organizational KM system so that others can access it, use the knowledge embedded in a work context. Simple. Straightforward value proposition.

Carlile and Rebentisch. Transformation->storage->retrieval. Transformation is better than acquisition because most reuse of knowledge is not as-is reuse; it tends to be modified/updated first. Adding context/metadata to knowledge in the system helps identify what is outdated/wrong the next time we need to use it.

Evans, Dalkir, Bidian. Identify->store->share->use->learn->improve->create. Incremental and radical (single/double loop) learning process like McElroy. Distinguishes between identifying existing knowledge and creating new knowledge (wow, revolutionary /s) and double-loop learning (which they stole from McElroy from 12 years prior why are they claiming credit). The process starts with an knowledge need. "learn is often overlooked in KM" is it though? I feel like that's been in every one of the processes we've described so far. The "silos of organizational learning and KM are brought together" what silos? Where you have introduced this dichotomy with a giant wall between these two concepts? Organizational learning has been in most of the definitions of KM and half of the process definitions! Connecting specific tools to different stages of this process.

One example is provided by Xu et al (2010), who discuss how knowledge integration (which they refer to as "internalization") provides the basis for repeated iterations of the knowledge processing steps through innovation.

What the heck is this? (Knowledge integration) provides the basis for (repeated iterations of the knowledge processing steps) by means of (innovation)? Innovation is a result of doing knowledge processing over and over, which is enabled by knowledge integration? What the hell does that mean?

Innovation cannot succeed without organizational learning, which in turn cannot take place without knowledge processing.

Okay but you just said that organizational learning was siloed away from knowledge processing. If that were true, no one could innovate at all.

the role of both tacit and explicit knowledge is quite prevalent in the processes involved with continuous innovation

but sadly is never explained anywhere.

So we've got this list of 10 steps that may all happen simultaneously. And then we condense that into 3 stages. Capture or creation is a separate stage from acquisition, why? Because acquisition actually means understand! Not acquire! The 10 steps the list on page 37 don't line up with the table of contents either.

Slides for week 3 KM Processes

Graphicalized representations of each of the processes. McElroy is second-generation? Wiig: organized, available, complete, accurate, timely. Collection development process criteria related? Carlile and Rebentisch "particularly useful in interdisciplinary collaboration" because transformation occurs as it crosses boundaries. Value proposition.

Chapter 3: Knowledge management models

Von Krogh, Roos, and Kleine Model of Organizational Epistemology: knowledge exists in the mind but also in the social links between people. Connectionists.

Nonaka and Takeuchi Knowledge Spiral Model: management of serendipity. If knowledge exists within a group, rather than being separate from people, the group can be mobilized to address issues with its collective knowledge. Tacit->tacit = socialization. Tacit->explicit = externalization. Explicit->explicit = combination. Explicit->tacit = internalization (finally, something individual-focused). Knowledge shouldn't sit still, it should cycle around these four processes. Continuous dynamic interaction between tacit and explicit.

Choo Sense-Making KM Model: Sense-making based on streams of experience, decision-making produces next knowing cycle, knowledge creating based on external information and knowledge. "Garbage can model of organizational decision making" indeed. "Good enough" decision making bounded by the realities of imperfect information and limited time. Knowing-doing cycle, knowledge-in-action model.

Wiig Model for Building and Using Knowledge: organization with a focus on use. Semantic relationships between pieces of knowledge. The more connections between pieces of knowledge the better, with a goal of a completely connected graph. This is asinine. The cost of toilet paper for the office restroom has nothing to do with encryption cipher selection or the color of our new branding efforts. 5 degrees of internalization of knowledge: novice beginner competent expert master. Public/shared/personal knowledge, +-coded and +-accessible, passive or active. Put this model in your own model! Goes beyond the tacit/explicit dichotomy.

Boisot I-Space KM Model: "1. The easier it is to structure and convert data into information, the easier it is to diffuse. 2. The less that data require a shared context for diffusion, the easier is the diffusion." Put your data in categories, the broader the categories the more abstract they are, and the more useful they are (then why have categories at all?). Codified vs uncodified, abstract vs concrete, undiffused vs diffused. "codification links to categorization and classification; abstraction links to knowledge creation through analysis and understanding; and diffusion links to information access and transfer." Scanning, codification, abstraction, diffusion, absorption, concretization.

Complex Adaptive System Models of KM (Beer, Bennet & Bennet): organization as living entity, intelligent complex adaptive systems (ICAS). Complex adaptive systems can "self-organize" emergent. There are lists of things that organizations need, processes and emergent characteristics, but apparently they "just happen". Why bother trying to manage anything then? Feels a bit "corporations are people."

McAdams and McCreedy KM Model: knowledge created by social interactions. Categories of KM models: k-sharing, km strategy, intel-cap. Want to balance a structured process with organic human interactions.

Knowledge-Sharing KM Models

Wang and Noe Knowledge-Sharing Model: environmental factors, motivational factors, individual factors, perceptions, knowledge sharing behaviors. Trust is important.

KM Strategy Models

Hansen, Nohria, and Tierney Model: codification for explicit, personalization for tacit.

Stankosky and Baldanza KM Pillars Model: leadership, organization, technology, learning.

Intellectual Capital Models

The Skandia IC Navigator model: useless, unexplained, non-obvious.

The Phronesis Model: SECI spiral? I am so lost. Phronesis greek for the type of intelligence or judgement that guides practical action.

Chapter 4: Knowledge capture and codification

Capture got talked about a lot in the process and models chapter. But what is it, and how do we do it effectively? It's typically considered the first step, since until knowledge is captured it can't be managed.

New knowledge can be created, existing knowledge can be identified. We need to capture knowledge we already know we have (like policy manuals), knowledge we don't know we have (observational studies of tacit knowledge), and generate new knowledge (to fill gaps). Need to handle both explicit and tacit knowledge. Codified means to make explicit, a structured standardized multi-purpose document.

Tacit knowledge identification

Ask everybody what tacit knowledge exists and who has it. If you can't ask everyone, try to be representative. Ask a team who their guru is for different topics. Do a social network analysis, who do you ask for help and who asks you for help? Review resumes and linkedin profiles to identify knowledge holders (expertise locator system). First pass via automation, analyze emails and chat histories and presentations etc. Tacit is highest value (citation needed) and thus desirable to identify first.

Three types of tacit knowledge:

  1. Relational, could be articulated if someone asked
  2. Somatic, contained in the body, hard to articulate and codify
  3. Collective, common knowledge or knowledge contained in the relationships between people, organizational culture

Type determines effort to codify, best approach to utilize. Practical: ask them. Reflective, get groups of experts to reflect collectively. Demonstrated: observe them as an outsider.

Tacit knowledge capture

For individuals and groups

New learning is exploration, using what was learned is exploitation. Intuiting, interpreting, integrating, and institutionalizing. Don't really know what any of these are.

Interview experts: structured (preplanned) and semi-structured interviewing. Questions provided ahead of time. Open vs closed questions, reflective listening (paraphrasing, clarifying, summarizing, and reflecting feelings). Non-Violent Communication? Case studies (tell me about a time when ___), key milestones, Why? questions. Can interview a group of experts at once. Delphi method: seek individual responses from the group, present the group an anonymized summary of the positions and their supporting arguments, ask for another round of individual responses, repeat as needed.

Ask about roles, responsibilities, tasks, utilized resources, references, contacts, other supporting content, list of people they interact with for different reasons, major lessons learned. May take a lot of rounds to fully scope everything. Transcripts are coded and thematic analysis. If multiple experts interviewed, resolve conflicts in responses. Consider visually modelling the results.

When are we done? When an interview round doesn't elicit anything new, when interviewer and interviewee swap places and see if there's adequate understanding, give the results to an unrelated person and see if they can use the captured knowledge.

Interviews have challenges: who are the experts, getting on their schedule, validating their responses. Must have both parties recognize a disparity of expertise. Delphi alternative, pass output to the right to evaluate and expand/refute, then pass back to the left to repeat.

Stories: a series of happenings, management actions employee interactions and other events, communicated informally with cultural context. Often are given spontaneously in interviews but can be elicited.

Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 51(4).

Not all stories are good for codifying and sharing knowledge. Need to be believable, authentic, compelling, evoke a response, concise. The moral of the story has to be understood, remembered, and influence future action. Useful for lessons learned and best practices. Desirable Difficulty, withhold the moral of the story and ask listeners to fill it in.

Non-structured interviews/learning by listening: have them tell you what they know without a preplanned agenda or question list. Reflective listening is used to validate the resulting explicit representation of the knowledge. Task analysis, process tracing (thinking aloud through a problem), simulations (asking the expert to walk through a constructed situational example). "Simulated teaching." Ask expert to provide most boring task they deal with, vs the most complex and difficult situation they deal with, and identify what makes them easy or hard.

Field study/learning by observing: motor vs cognitive. Video recording of an expert undertaking a task won't fully communicate the knowledge involved, but serves as a starting point. Screen recording for computer tasks. Can be gone over again and again. Rather than just recalling how to do the task, this can cause the expert to reflect on the task as its undertaken, which can subsequently be discussed and captured as well.

I've watched people undertake various car repairs. While I like my Haynes manuals, watching the repair occur in real time on a real vehicle is a different knowledge transfer experience.

Exit interviews (chapter 12), project postmortems (chapter 11). Peer assist (bring in people from outside the group to provide suggestions on a problem). Knowledge jams/innovation jams (cross-unit collaborative problem solving/idea generation); small teams, clearly defined problems, Prime them like in The Art of Gathering by Priya Parker (shoot I bet a lot of things from that book would apply to this chapter), make it fun.

When doing interviews or observations etc, keep the primary sources! A chat log, zoom recording, whatever. If you're doing a postmortem of an incident, summarize the key points etc on a wiki page but link the recording and transcript as primary sources. And send the recording/transcript to the person recorded for validation.

At the organizational level

Assumes most capture has been done and we can jump straight to codification. Organizational culture, mentoring, collaboration, documents, meetings, informal groups, experiential training, professional and social networks.

AI can draw all the conclusions for you, just feed in your clinical findings and outcomes and it'll make you a fancy flow chart so you don't even have to read.

Explicit knowledge codification

Documents "constitute the only real corporate memory of the organization" seems reductive. A conversation that shares knowledge between two people is explicit already, but that doesn't scale, so we want to put stuff in documents. Documents need to be accurate, readable, understandable, accessible, current, authoritative and credible.

Cognitive maps

Nodes are key concepts, links represent interrelations between concepts. Captures views, perceptions, judgments, hypotheses and beliefs of the interviewee. Two dimensional graphical form.

CommonKADS

Knowledge Acquisition and Documentation Structuring:

  1. Task model of the process
  2. Agent model of knowledge use
  3. Knowledge model of the knowledge to use
  4. Communication model for between agents
  5. Design model for architecture and technical requirements

Decision trees

It's a flowchart like we had for clinical decision making.

Knowledge taxonomies

It's a tree. A hierarchy. Knowledge dictionary/glossary for important terms and jargon (isn't related to the taxonomy! why are you discussing it here!) "the useful lifespan of knowledge should be quite short" oh really? Why?

The second step in compiling a knowledge dictionary is creating a knowledge taxonomy.

What's the first step? What other steps are there? Taxonomies are created by consensus and must use the terms workers actually use in the execution of the organization's operations. Perfect consensus is rarely possible. Now they've decided to talk about thesauri? Techniques for creating a taxonomy manually: Card Sorting (Nielsen, 1994) and affinity diagramming (Gaffney, 2000). Both involve making cards and grouping them. Can use Delphi to validate. Cluster analysis, but how does that apply to non-euclidian things like this?

Can theoretically be created as something other than a hierarchy. Folksonomies are too informal for use in an organizational taxonomy. Can do hybrid, fixed taxonomy at top of hierarchy and folksonomy within the fixed leafs.

Task analysis

Not present! Who edited this thing!

Live class 2025-10-23

Discussion of assignment 2 (probably need to get started on that, it's a long one but I can use an existing scenario so that won't be awful). Looked at Indigenous knowledge management tools (without creating accounts) and discussed differences between them vs Western stuff we've interacted with (Indigenous character sets, terms of use summary). Thought exercise: what categories, specific questions, and knowledge transfer techniques would you use to handle her retirement succession? Unreasonable to expect knowledge transfer to happen on top of other duties, but we live in late stage capitalism. Do you owe the organization this knowledge/effort? If you do this kind of documentation all the time as part of the job duties, you don't pay the significant cost to capture it at the end, and they don't walk out the door without you having a copy of the knowledge.

Chapter 5 Knowledge Sharing

In summary, a CoP, mentoring, storytelling, succession planning, coaching, and knowledge repositories (in decreasing order of effectiveness) are the most effective for sharing knowledge in organizations. Studies may vary their ranking, but most confirm that long-term, face-to-face interactions in real time and in proximity are much better at sharing knowledge in general and tacit knowledge in particular (e.g., Mazorodze & Buckley, 2020). Interacting via technologies reduces the media richness and social presence to the detriment of knowledge-sharing effectiveness. However, not all technologies do so to the same degree.

When the KM portal tool is difficult to use, people don't use it, and find other ways to share knowledge.

Communities of practice and some of the specific instances they talk about like world café remind me of Gathering thoughts.

Indigenous knowledge systems and their role in communication

Leveridge, D. A. N. (2024). Indigenous knowledge systems and their role in communication. https://pressbooks.bccampus.ca/communicationstrategies/chapter/indigenous-knowledge-systems-and-their-role-in-communication/

As a settler scholar, my perspective is shaped by Western academic training and by my lived experience within colonial institutions. I approach Indigenous Knowledge Systems with humility and respect, recognizing that these systems are diverse, place-based, and held by Indigenous communities themselves. My role is not to define or represent Indigenous knowledge, but to highlight its importance and encourage learners to engage directly with Indigenous voices, sources, and communities wherever possible. I remain mindful that writing about Indigenous Knowledge from a settler position is inherently limited, and I encourage readers to approach this material as a starting point for deeper learning, dialogue, and respectful collaboration.

Good positional statement I think.

Oral tradition and storytelling. Symbolism and ceremony. Respectful dialog and consensus building.

Collaborative land management. Traditional ecological knowledge in conservation.

Respecting intellectual property rights. Cultural sensitivity and reciprocity.

Where did the rest of my notes go?

Week 7 was AI. I hated most of this.

Week 8 was organizational culture and continuity management, chapters 7 and 12. Culture is important and leaders create it by example. Tell stories. Continuity management shouldn't be started when someone announces they're retiring or turns in their 2-week notice.

Week 9 was evaluation, metrics and measurement, chapter 10. A variety of evaluation methodologies were considered, benchmarking and scorecards and "house of quality." Social network/graph theory stuff was mentioned. None in much detail, not actionable. Beware of Goodhart's law.

Week 10 was future and EDIA, chapter 14. This chapter has no headings, just a big block of text. DEI topics can promote feelings of safety that help people be willing to exchange knowledge, and having diverse input into KM efforts makes the results better. Still all about the benefits to the organization.

Bonus content: finding knowledge, technology and software, chapter 6.

Bonus content: strategy, management visions, IK policy framework, chapter 9.

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