September 13, 2009
You know, I think that I've become a feminist. I've been mulling over the idea for a few months now ("Huh? ME? A feminist?"). I also stumbled on a resource, "Finally, A Feminism 101 Blog", and reading some of the entries here helped to educate me about feminism. Now that I know what feminism is, and formed an opion about my personal stance on the matter, and now that I've sat on it long enough for the idea to "feel" right, I'm going to say so. I'm a feminist!
I think that the turning point in my feminist thinking hit its crux about 4 months ago. I was participating in a discussion about artificial intelligence in a computer science forum when one of the contributors casually mentioned that they'd read about a similar topic in "Maxim" a while ago. I didn't know what Maxim was, and thinking it was some cool AI magazine I didn't know about, I Googled.
I raised an eyebrow when I found the online magazine's current headline, something to the effect of: "Cheerleaders, give me an H, O, T!" Maxim is a men's magazine that shows pictures of scantily clad women (with other content too, but...). Could this be what the contributor was talking about? Why would the contributor mention this magazine name in an AI forum? I thought it was totally off topic, and it made me uncomfortable.
And, as I do when I am uncomfortable, I overthink: What was this contributor trying to do? I thought that since the forum was frequented by undergraduate computer science students (a good chunk of whom are 18-20 year old young men), perhaps this poster was trying to impress peers by announcing that they (he?) reads this "grown up" sort of magazine. I don't know.
Anyway, I was distressed for quite a long time afterwards. Not severely distressed of course -- I was able to get on with my life and forget about it, for the most part -- but every now and then the thought would bubble up, "Should I have said something?" But what would I say? I didn't want to embarrass the kid in front of all of his classmates, nor did I want to seem like a prude for yapping about something so "trivial".
I never did bring it up, and the thread has since been archived. But I still veer toward feminist sites to see if other people have encountered a similar situation. Maybe I could figure out why it distressed me, and if anyone out there had advisements on how to handle it.
I still don't have a solid answer. But I CAN point out some articles that spoke to me:
Isn’t feminism just "victim" politics? Not long ago, even as recently as a couple of years ago, I had secret thoughts that feminists were just a bunch of loud-mouths looking for attention, crying "poor me" when they didn't actually have anything legitimate to complain about. The more I read and the more I listen, the more I believe that I was wrong.
“Feminists Look for Stuff to Get Mad About” Following the line of thought above, I found myself in the past thinking that feminists who made a point about using inclusive language or pointing out a seemingly trivial wrinkle in public policy were just looking for excuses to complain and were "annoying everyone with trivialities". I think I'm starting to change my mind.
When Worlds Collide: Fandom and Male Privilege I didn't know what male privilege was before reading this. Reading this article gave me a perspective I've never seen before, and it struck several chords of common experiences in my past. I don't know how to react to it yet. Learning about male privilege has also illuminated me to the concept of "white privilege", opening my eyes even more to the privileges I enjoy myself, unaware of the challenges that other people have to face that I don't. (update: another resource about male privilege)
Another article, taking the same tone as above but with a new level of eloquence and fire, by Melissa McEwan: The Terrible Bargain We Have Regretfully Struck. It's worth a read.
Anyway, I'm still in the "input" stage in my feminism: learning, deciding, analyzing.... but this is a case where I'm seeing that knowledge IS power, and the more I learn about this issue, the better equipped I will be to deal with the daily things in my life that make me uncomfortable. If I can see why, and learn how to do something about it, I think I'm taking better control of my own world.
Where I live (Montreal), women keep their family names by default. The couple gets to choose how to name the kids, and one valid approach is to use both last names with a hyphen. In fact, the lady has to go out of her way to change her name.
When we lived in New Brunswick... I was called "Mr Lampron" because nobody could believe that my wife could have a different last name. Well... don't go live in New Brunswick...
Yes, there are fewer women in most TV shows, including Atlantis. But there are exceptions. I'm thinking about a cool vampire slayer... What fantastic ladies! And the show has been written by a man.
Posted by: Daniel Lemire at September 14, 2009 03:34 PM
I think you are right, Daniel... it shows that things are moving in the right direction! And Buffy is cool. :)
Posted by: Steph at September 15, 2009 08:46 AM
Steph, great post. I'm glad to read this! While all feminists encompass a spectrum of reasonable to overboard (all depending, of course, where you draw the line between the two), a common complaint amongst feminists is when fellow women believe they are a bunch of whiners.
Those who are fortunate enough to have not faced much adversity (myself included - I've been very lucky) shouldn't discount the things that have happened to others, or institutional problems that could easily affect everyone.
Because even I, who have been very lucky, have been asked by my superiors if I "like sex." It was an isolated incident, and I can brush it off, but it's still messed up. Realizing that that (and worse) happen regularly to others is what gives me a feminist bent.
Have you ever thought about joining Systers? Check it out.
Posted by: PhizzleDizzle at October 21, 2009 01:18 AM
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Index to Steph's NotesFeb. 24th 2007 - Weee! This new part of my website is not an entry, but rather a permanent fixture whose purpose is to "Look Down on All Those Notes With Some Grand Vision of Organization". Wish me luck. LOL
- Representing meta-data (fuel) & the different kinds of "hooks" that intelligent systems can use (how fuel is injected into the motor of the engine)
- Motivation: Semantic net / Rationalizable to a machine
- Semantic network
- Genetic graph
- Prerequisite AND/OR graph
- Constraint Satisfaction Problems
- Bayesian networks / causal graphs
- Technology & Philosophy: RDF, modus ponens,
- Predicates, Logic & situation calculus
- What kinds of data? - What kinds of meta-data would an AIEd system possibly need, and how is it represented?
- task domain knowledge
- "is-prerequisite-to"-type knowledge
- interactions with learning objects & other learners - (location, composition is-a/part-of, sequencing by restricting navigation, personalization, ontologies for LO context)
- lesson plans, curriculum plans, practicing sessions (What is stored, what is generated on the fly? What is remembered?)
- How to organize it - When is it stored in a database? Meta-data? Agent memory banks? Protocols? Repositories? XML files? Home-servers? WSDL services? Frameworks? Portable banks? P2P access?
- Database of object-agent interactions
- Concept of "Home" on a P2P network -- maybe the bulk of a learning object's usage data is on its home server and can be queried using WSDL or something ? Similar homes for each student's usage history, etc. Baggage problem.
- Links to the ontologies
- referring to a concept/relationship - ex. AgentOwl?
- Generation of this data
- Rationalization: For use by other AIEd systems
- What is generated - discuss items under part I.C.
- When it's generated - describe procedural model, which parts of the engine generate what (isa-part-of data, XML feeds, web services, meta data bout groups and collaboration, protocols, examples Friend of A Friend FOAF project)
- Technical notes of HOW it's generated: JENA, issues of implementation demo, my Hermione & Ron agent examples, lol
- Usage of this generated data - see part IV. A.
- Given the engine, who uses it?
- Students / Learners / "Me"
- instructional planning, student model, pre-requisites, tutoring, coaching, collaboration,constructivism
- Teachers / Educators / "Me"
- putting together lessons
- be able to browse through task domain knowledge in an objective / encyclopaedia format, then be able to pick-and-choose what you need for your students
- compose examples, design explanations, pull together diagrams, learning objects, etc. Haystack Relo?
- Administration / Governement / Structure / Crowd Control
- as restrictions/obstacles/sand pit to the robot in agent environment
- can't just have a swarm of students and teachers out there -- need structure of courses, curriculum, objectives, requirements (at least, we do in this day and age!) - Report cards, evaluation, feedback
- government, marks, certificates, requirements, funding, curriclum, attendance, delinquent, non-attending, motivation
- school''s images, goals, strengths, payroll, HR, security, accounts, permissions, privacy
- registration, failed courses
- User Environment -- How does this engine work? What does the user see on the screen?
- Introduction - Given a background in educational psychology, how does the system present itself -- what does the user see, and were does this data come from? Links to thoughts from part I.)
- Task Domain Browsing - Suppose you're you're just idly browsing through the "raw" content. How would it look when it's not wrapped around a learning-context or lesson or tutorial or anything. 'Cross between browsing a raw task domain ontology and browsing a learning object repository.
- Cleaning up the data -- Visualizing the data for humans to pick through the task domain and work on it. Suppose the "Subject Expert" discovers an advancement in science and needs to update the "world's" domain knowledge. (I used the "Subject Expert" terminology from Ontologies to Support Learning Design Context - Thanks Chris) How would they make corrections to ontologies and learning objects, or at least point the users of "old" objects towards adopting the newer ones.
- "Modes" - Learning & Lessons / Checklist - Homework, Assignments, Courses being taken / Collaborative mode / Teaching mode / Calendar- email -adminisrative mode -- See also the different kinds of scenarios in the ActiveMath system
- Evolution of this engine
- target some key implementation hooks discussed in part I - design an experiment/demo
- scrape a page - (Note, scraping can only give objective data, not in-context dat)
- LO repository - related to browsing the task domain?
- a learners "To Do" list - where does it come from? Assignments, courses.
- sample group scenario
- sample teacher lesson planning
- sample data "left behind"
- sample use of that data
- Data mining (for what? lol )
- discovery / generation of ontologies - when do you need to hunt for them, and when do you have to have a solidly-known & predictable ontology?
- I/O - where it happens, which languages, protocols, which agents perform i/o and when, precepts, actuators
- Role Assignments
- My Environment Adapts to me
- Displaying feedback from the server on JSP pages (Software engineering considerations)
- Sketching out a design (Content planning vs. Delivery planning)
- agent negotiations / social structures / ummm... Web 2.0 ?
- garbage collection of meta data
- Artificial Intelligence & Evolution
- Memory Culling: Necessary part of intelligence? (artificial or human)
- Applications for the Genetic/Evolutionary algorithm
- open learning environments
- Agents, pets, grouping, Community modelling
- Protocols - finding groups, cyber dollars, state diagrams (?)
- "Community Studies" - graphs & communication hubs, types of communities (free-for-all, hierarchy of authority, etc.)
- implications of joining a community - what do you share, which parts of your student model are relevant
- Walls & sand traps -- deliberate restrictions as problem-solving for learning
- Communication channels - individual-to-individual, individual-to-community, chat channels, agent-only "administrative" communications, ex. requests for related learning objects in a particular community, etc.
- Educational/Pedagogical focus (this part probably shouldn't be its own section but rather incorporated into the whole picture, but it's separate for me right now because I'm still only just starting to learn about it.)
- Semantics - what there is to talk about in Education
- ex. Merril's First Principles of Instruction, linking educational terms to AI terms
- Pedagogical skills for tutors -- supporting human *and* artifical tutors
- Student modelling - what the machine needs to know about the student, pedagogically-speaking, about learning history/preferences
- Roles - Simulated students, Coaches, Tutors, Teachers,