Tuesday, October 1, 2013

Assessing Collegiality in the Workplace: Holy Grail or Red Herring?

Universities can be notoriously un-collegial places to work. This is especially true for women in academe. Earlier, I wrote about mommies in academiaToday's post builds on that post and examines how discussions and initiatives about collegiality in educational settings impact females in academia. Today's post mirrors and extnds my December 2013 Women's Caucus column for the NAEA (National Art Education Association) NAEA NewsThe image below expresses my own thoughts about women's work in the ivory stable; the detail is a little pun for my art ed friends. 
Milking the Red Herring. (2013)
From Peasant Woman Milking a Cow. (13th century England)

Detail: The Holy Pail

The term collegial is derived from the root word college, and from the Latin word collega, meaning “colleague”Rightly so, an expressed desire for respectful, supportive, engaged colleagues permeates schools' and universities' mission statements and evaluation policies. By all accounts, collegiality amongst faculty members is seen as essential for the productivity and well-being of an educational institution and the people who work there. But the fact is, toxic co-workers and incivility pollute academic departments across the US. Noncollegial co-workers bully their fellow faculty members and students, gossip, complain incessantly, resort to threats and personal attacks to get their way, refuse to share equitably in menial departmental tasks, and execute a host of other destructive behaviors in pursuit of their own needs. Universities are legally empowered (and some would argue morally obliged) to evaluate and hold faculty members accountable for their collegiality (or lack of). Apparently, the jerk-problem in academia has gotten so bad that there is currently an initiative afoot (and for sale) to assess an individual faculty member's collegiality in university settings as a criterion for promotion.

The goals of promoting collegiality and holding faculty members accountable for their behaviors toward one another are both laudable and much needed. But many challenge the idea that collegiality can be objectively assessed via standardized matrices and direct attention instead to ways that institutions militate against collegiality. It is important to note that in choosing this profession aspiring scholars/educators have envisioned as the core of university life the rigorous pursuit and advancement of knowledge in a creative, intellectually challenging environment. They aspire to make a difference in the world. What disillusioned academics have found instead are grueling workloads, job insecurity, inadequate compensation, a capricious and opaque system of institutional rewards and punishments, a worksite mired in conflict, and administrative bloat and ineptness. The problems resulting from entrenched institutional policies and practices that at best can be described as deeply flawed are now compounded by strained resourcesdiminishing public support, and a relatively new competing paradigm that positions the enterprise of public education as a business venture rather than a common public asset. Budget cuts, institutional red tape, inequitable work loads, demands to publish, and mind-numbing committee work are now commonly shared sources of stress for faculty members across types of institutions. Intensified public attacks on the work university faculty is an additional stressor. In such an environment, collegiality, which is fundamentally about how faculty members treat one another, is significantly compromised. 

Bad faculty behaviors in academic institutions are exacerbated by the fact that the lynchpin for attempts to maintain a civil, collegial atmosphere in the university worksite is the departmental chair, someone who is oft times a former faculty member who is given tremendous responsibility and power but who possesses minimal administrative skills, receives very little training for the job, and holds limited power within the larger institution. Worst, yet, in dealing with departmental faculty bullies and even exhibiting bullying behaviors themselves, mid-level administrators may in fact be part of the problem, not part of the solution. University Human Resources departments (often stated in university policies and procedures manuals as the best place for faculty members to report bullying and seek redress) may also be perceived by faculty members as ineffective and more interested in protecting the institution than the well-being of victims of bullying. 

Conducting an evaluation of individuals' social interactions in absence of full consideration of the institutional and administrative policies, procedures, and contexts in which the performance of their responsibilities occurs is inherently hypocritical, conceptually unsound, and bad social science. Usage of standardized collegiality metrics for promotion or merit considerations further erodes one of the purported strengths of the academy: academic freedom, discourse, and dissent.

Understanding and promoting collegiality in the Ivory Tower is an important but complex matter. Assessments of collegiality pose particular issues of concern to female educators. Any institutional evaluation of a female faculty member's collegiality must include consideration of workplace-embedded gender inequitiesgender stereotypeswomen's professional communication styles,  and the institutional contexts in which women conduct their business. The facts clearly warrant such consideration: women educators earn less across academic disciplines and at every level of teaching, they hold lower ranks and fewer positions of power within their educational institutions, they are bullied more and supported less than their male counterparts, they endure longstanding institutional policies that are inherently anti-family, and gender stereotypes, discrimination and evaluation bias continue to impede women's advancement in the workplace. 

In conclusion, attempts at capturing collegiality on a standardized matrix designed for efficient assessment of an individual's performance of their responsibilities and then using that measurement in faculty evaluations is an ill fated endeavor with little promise of improving the working conditions of female faculty members. As a largely female-dominated profession art educators need to conduct and disseminate research that focuses on how female educators’ experiences within varied institutional contexts, pre-k through post-secondary, impact their productivity and performance. The most relevant studies from the discipline of art education addressing this concern are either a quarter century old (Rush, 1989) or they just don't dig into workplace inequities impacting female academics (Milbrandt & Klein, 2010).  Most of all we need to understand how our own workplace conditions shape our social interactions and both facilitate and impede our success.


The Holy Grail - Red-Herring title for this post captures my thoughts about attempts to assess collegiality in terms of any faculty member's behaviors, male or female. But the image is deliberately of a female for obvious reasons. The close-up detail of the "You Gotta Have Art" button is a nod to and a bit of insider-humor for my colleagues in my profession, art education.

Blogs are awesome in that one can add to anything written, written even years ago as this blogpost was originally written by me in 2013. I'm adding to this post a reference to a recent (2019) news article that is particularly relevant to my former place of employment. The article, published in our local newspaper, recounted the efforts and ultimate success of a female working at my former university as she sought and received salary equity. In one of the articles I read in the local paper, professor McDonaugh recounted what she was told by the Director of the unit at the time (a female Director). When she requested a salary equity raise, her Director told her that she didn't need to be paid as much because she didn't have a family to support. That statement became part of professor McDonaugh's lawsuit. Salary equity is a peripheral issue to the problems of assessing the collegiality of females in the workplace, but they are all part of the same system that I described in this blogpost...a system that...well, you already know.

Ziterman, B. (June 27, 2019). UI professor who sued over gender-based wage discrimination gets back pay, raise. Champaign, Illinois: The News Gazette. https://www.news-gazette.com/news/ui-professor-who-sued-over-gender-based-wage-discrimination-gets/article_d14ebb61-2a83-5087-bf02-c7acac0626df.html

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Thursday, May 9, 2013

K-12 Art Teaching and Magical Thinking

I've been getting works ready for the "Those who teach, can" exhibition at Indigo Artist Coop in Champaign, Illinois, May 10 - 18, 2013. Opening reception, Friday May 10, 6 - 9 p.m.

For one of my works, I selected 16 images from over 200 pictures that I took on my iPhone4 documenting some of my experiences teaching Art Survey 1 at Centennial High School during the 2012-2013 school year. My idea here is to convey a sense of a “year in the life of a high school art teacher”. As I took each of the pictures appearing in this series, I shared my favorite ones on Facebook, Flickr, Tumblr, and Instagram; and I even Tweeted some of them to my friends in Twitter. My iPhone camera roll (now totaling over 3000 images) is filled with these kinds of photographs, along with shots of family, friends, events, sunsets, my garden, favorite personal objects, and some creative explorations with various photography apps. I originally thought to exhibit these in a grid, similar to how I see them on my iPhone in my Instagram app.

But then, I decided to exhibit them on a timeline in order to better convey the "year in the life of an art teacher" idea. I took a quick snapshot yesterday as we finished the installation and posted it to Instagram.

There is something both ordinary and extraordinary about all of this…about visually capturing and sharing experiences so easily through digital and social media, about printing ones own photographs and presenting them for public viewing in an art gallery, about working with like-minded colleagues in our endeavors to make art with creative young people, and about being an art educator with a mission to make a difference in the lives of others. I have always thought K-12 art teachers to be people who engage in a bit of “magical thinking” when it comes to what exactly it is we do, and all I can say about that is “please let there be more magical people in the world!

Saturday, May 4, 2013

Anyone-an-artist, DIY culture, and Selfies

I put together a couple works for the "Those who can, teach" Champaign Unit 4 Art Teachers exhibition at Indigo artist coop. May 10-18, 2012, 9 East University, Champaign. The image below is one of the works I exhibited, a composited collection of my Facebook mini-collages (Selfies) that I created over the past 3 years. My other image was a collection of snapshots I took during my year of part-time teaching (2012-2013) at Centennial High School.

What are Selfies? 

Selfies are self-portraits taken with inexpensive digital or cellphone cameras (sometimes taken with mirrors, other times not) and posted on social media sites such as Facebook, Twitter, and Instagram. Self-portraits are nothing new in the art world. What's new is the fact that the age of digital and social media facilitates a virtually infinite number of self-portraits to be created and shared with viewers online, and that the creators of these self-portraits are not traditional art-world or academy-trained artists, which is to also say that their self portraits have little economic value. My recent hashtag search in Instagram for the #selfie hashtag and its variants produced around 35 million photos, and a search for the #me hashtag in Instagram produced over 44 million photos. These are astonishing numbers by anyone's count.

Selfies are characterized by bloggers and social media commentators as annoyingnarcissistic, insufferable, and ridiculous bordering on offensive. Selfies are also recognized as a resistanttransgressive, an empowering form of self exploration and personal creative expression, and a visual diary marking our existence in the world. There are apparently even rules for doing selfies. Although I doubt if very many of those folks who have posted over 35 million selfies to Instagram are paying attention to anyone's rules, some interesting trends suggest an the emergence of an online-world aesthetic when it comes to portraitsfemales' and males' selfies. Setting all these debates aside, what remains clear is that selfies are an unashamed way of saying it's #me, I'm here, please look and like!

My creative process for making selfie-collages

For my original self-portrait image I used my laptop camera, sat at my dining room table, positioned the laptop lens, and took a pic of myself.  I shared my self-portrait in color and in black and white with various folks at the NAEA who needed an image of me. With the original in hand, I started making these selfie-collages in 2009, which was about the same time I joined Facebook. My original profile pic on Facebook was a snapshot of a Christmas ornament that I modified in Photoshop. I just didn't feel comfortable in 2009 sharing a pic of me on the Internet. (LOL, I soon got over that feeling.) 

Each mini-collage selfie took anywhere from 2 - 3 hours to create and refine. The process (described below) was exacting, but lots of fun.
  • In addition to the original self portrait image (mentioned above) I took pictures of subject matter that I wanted for the collage (computers, cornfields, airplanes), initially using my inexpensive digital camera, and later using my cell phone camera.
  • I also searched online for other images of subject matter I needed (soccer ball, TV set, pic of the state of Florida, etc.)
  • Using image editing software (Photoshop in my case) I isolated (cut and saved as a separate image file) the part of the image I wanted to use.
  • I then modified each image to be collaged. I got rid of unwanted background content; cleaned up the edges of the remaining image; and played with size, positioning, saturation, color, contrast, sharpness, levels, etc. 
  • I then pasted each modified image onto the self-portrait image (using Photoshop's layers tool).
  • I further adjusted each of the layered images to create my desired effect.
  • Once I had something I liked, I saved that file to my computer as a .psd image file (layers intact).
  • I then flattened and saved the digital collage, paying attention to format (jpg, png, tiff), resolution (DPI), and dimensions (height/width) settings. I gave each version of the image its own file name.
  • I usually made two or three variations of the collaged final image. Each version had its own file name.
  • Because these were for Facebook, I kept the dimensions and resolution low, but now I keep larger versions of each collaged image as well.
A couple more tips

In 2011 I abandoned the use of a digital camera and Photoshop to create these selfie-collages. I now take pics with my cellphone and use Preview (an app on my Mac) and Pixlr (a free online photo editor) to create these collages. The process is the same as when I used Photoshop. I archived most of my Facebook mini-collages to a Flickr set. These are all small format images. I wish now that I had created them larger (dimensions and resolution), saved the larger files, and then reduced their dimensions for Facebook.

For the art exhibition, my interpretive wall text for this image talked about FacebookDIY-culture, apps, and the popularity of "selfies" in social media sites.

Regarding the "Those who can, teach" show... (a smart title for this exhibition of Unit 4 art teachers put together by local high school art teacher, Stacey Gross) all I can say about recognizing the artistry, creativity, and excellence of our teachers (all of them, not just art teachers) is that if we want good folks to choose this profession, we better start supporting them, and on that standard, I give America a big fat "F".

Tuesday, April 23, 2013

Capturing and Characterizing Instagram

My previous posts have talked about my fascination with both Twitter and Instagram. 

But how does one analyze the behaviors of a community consisting of 90 million users who post 40 million images each day?

Last February, I tried a little experiment to see if there was a way to use Twitter to "capture" the nature of Instagram images. For about 30 minutes, I simply watched what got Tweeted with the #instagram hashtag. Inspired by what I was seeing, I collected some of the coolest images so I could go back and view them later. In order to group the images  I liked, I re-tweeted those Instagrammers' Tweets that caught my eye, adding my own hashtag #15minutesofinterestinginstafindsontweetdeckfeb192013 to each of my retweets. I used an app called Tweetdeck, which allows me to see the Tweets of several different hashtag groups on one screen, each group in their own column. With Tweetdeck and my ridiculously long hashtag, I now had a collection of my favored Instagram images that had been shared on Twitter! Later I went back to my hashtag collection, nicely grouped together in a Tweetdeck column, and looked at what I all had gathered.  By clicking on any Instagram image appearing in the Tweeted (and now retweeted) message, I could see any image full size and displayed on a webpage (an Instagram page).  I shared some of my findings about Instagram in my Feb 17, 2013 blogpost and in one of my presentations at the Annual conference of the NAEA in March 2013. My snapshot of Instagram suited my purposes at that time. I selected what interested me and shared my findings.

What if someone wanted a more definitive "snapshot" of Instagram? How might one collect a more representational sample of Instagram images (images that were posted to Twitter)? And what procedures might one employ to understand kinds of images one finds on Instagram.  Answering this question beyond the obvious is no easy task, since by recent estimates nearly 40 million images are posted in Instagram each day. 

Today's post poses one possibility. I'm calling this procedure An Instagram Snapshot in Time (on Twitter). This procedure relies on the fact that Instagrammers appear to like Twitter, which is to say, they like having an audience. I've had to modify my strategy since last February, since Instagram images no longer show in Twitter streams. 

Here are my recommendations.

Data Gathering: Image selection
  1. Establish a set time span for collecting images tweeted with the #instagram hashtag. For example, 6:00 a.m. until 6:20 a.m. on a certain day (I used Feb 20 in my example).
  2. Retweet each #instagram Tweeted post, giving your retweet your own hashtag.  I recommend a descriptive hashtag with a date such as #IG_feb20_6am
  3. Work fast. Instagrammers are uploading a lot of images and Tweeting about them. The Twitter stream will move rapidly. If you miss retweeting an #instagram Tweet, grab the next one. 
  4. Once your timed session has concluded, you can see all of your Retweets together in a Tweetdeck column or on your regular Twitter web page. Learn to find and display tweets with a specific hashtag to see your retweets. Twitter and Tweetdeck will display your specifically hash-tagged retweet, filtering out everything else in that display. Retweets will display this way only for about a week.
  5. After about a week, to see your specifically hash-tagged retweets, you will have to go back to all of your tweets, and look for those that you retweeted on a specific day and time. 
  6. Next - capture the URL for every image that was tweeted with the #instagram hashtag during the timespan you retweeted them. Follow the link from each original #instagram Twitter post (that you had retweeted) to each URL. The URL will most likely be a web link to the original Instagram image. Copy and paste these URLs (from Twitter) onto a list you create in MS Word. Using your list, you can now go back and look at the images that are found at these URLs. Your Browser History will also have these URLs.
  7. Repeat the procedure at noon, 6:00 p.m., and midnight so that the Tweeted Instagram images are more likely to have come from IGers living in different time zones (IGers are from all over the world).
Organization of Data: Create a Data Archive 
  1. Go to each URL (web page containing the Instagram image) given in the Tweets during your time span (and that you have now either have in your browser history or listed by URL on a list that you created). 
  2. Capture or download the image and accompanying text appearing on each Instagram web page. 
  3. Create a labeling system for each image as you capture and archive it, for later analysis. For example, relabel each image file with an easy to understand label such as IG-1_feb20_6am.jpg; IG-2_feb20_6am.jpg , etc...  The underscore symbol makes the file label easier to read. 
  4. Create a list of the Instagrammers whose image you have archived, identifying who created IG-1_feb20_6am.jpg, who created IG-2_geb20_6am.jpg, etc.  Use their IG names.
  5. Create a short profile for each Instagrammer, following their Tweets and Instagram uploads to their profiles, and then to their websites or other social media accounts. Obtain as much information as possible by reading their profiles and following their links.  Who are these folks?
Creating an Image Archive through Online Curation

Once Instagram images have been identified for inclusion in a study, it would be great to be able to see the entire set all together in one place. There are may ways to curate a collection of images found on the Internet these days.  One of my favorite tools for curating collections is Pinterest.

To create a collection online of the Instagram images that had been tweeted with the #instagram hashtag, I spent about 20 minutes retweeting these #instagram tagged tweets so I could go back to my Twitter account later to see what all I had. Then, on my Twitter page of my own Tweets, I followed each of my retweets to each IGer's instagram image. Once I was on the site where their Instagram image was displayed, I pinned each image to a Pinterest board. Under each pinned image, I also included the number of likes and comments each image had generated within about a month since the IGer first posted the image. Instagram is dynamic. Anyone that sees an Instagram image may continue to like and/or comment on the image long after the image is originally uploaded to Instagram. As a result, Instagram likes and comments are not a static number, and the number of likes and comments I provided under each image in my Pinterest collection may change over time. Therefore, I recommend doing this procedure a week later in order to capture likes and comments. After about a week, there will likely be few additional likes or comments for a specific image.

Below is a screen capture of part of an Instagram image archive I created in Pinterest from Instagram images that had been tweeted with the Twitter hashtag #instagram on Feb. 20, 2013.  I called my Pinterest collection (aka "pinboard") "An Instagram Snapshot in Time, February 20, 2013". The use of the term "snapshot in time" is intended to convey that this was a strategy that captured Instagram posts to Twitter at a particular time. My entire Feb. 20, 2013 collection is now available in one Pinterest pinboard at http://pinterest.com/edelacruz/instagram-snapshot-in-time-feb-20-2013/

Figure 1: An Instagram Snapshot in Time, February 20, 2013

Data Analysis: What can we say about Instagram imagery and their creators? 

Instagram images are anything goes! They will be fun to describe, code, and sort. The process is inductive, but systematic. There are numerous writings in research methods discourse that explain how to analyze qualitative data in order to make sense of it (Guba & Lincoln, Patton, Maxwell, etc). Commonalities across those writings about data analysis methods include closely reading the material gathered, describing the material, coding it, categorizing and grouping similar content together, identifying patterns that emerge, and explaining what's there based on these aforementioned procedures. 

At the onset of any study of Instagram, I'd be curious to know what these images are about and what aesthetic qualities they have. What is their subject matter? What are their aesthetic qualities? How many Instagram images are totally abstract, partly abstracted, or realistic? How many are "selfies"? How have they been manipulated using apps and filters? How many are closeups, mid-range, or far away shots? 

In attempting to answer these kinds of questions I would use procedures that come from art criticism and art history. Art critics and art historians often talk about subject matter, meanings, visual qualities, processes, conventions of style, the context in which the art form was produced, biographic information about the artists, and intended audiences.  Researchers in engineering and empirical aesthetics have also attempted to describe images and (using statistical methods popular in social science research) explain how they are understood or appreciated by audiences, but their methods are not particularly robust. Art history and criticism use empirical methods that are qualitative, narrative, and more authentic and convincing: description, image analysis, identifying conventions of style, and finding out about the creator of the image. Using art criticism strategies, I recommend describing Instagram the images with short phrases or single words that identify subject matter, compositional strategies, and aesthetic qualities in each image. Each image will have multiple descriptors (which can later function as codes for analysis purposes). A table of images and their descriptions is a must. The table would include the image label and identify its creator. Possible areas for description and analysis might include but are not limited to the following:
  • subject matter
  • composition, framing strategies, and depth of field
  • formal qualities such as color, pattern, lighting, or texture
  • degrees of realism or abstraction
  • kinds of transformations made to the photo through apps and filters
  • locations where the pics were taken (if discernable or described)
  • the content of the text that gets tweeted with the image
Like any qualitative research, content that seems important enough to become a descriptive category should be shaped by the data itself (the images). The descriptors heading the rows in the Table 1 below are just a starting place.  
    Table 1. Describing Characteristics or Attributes of Instagram Images

                                   Data Analysis: Coding of Instagram Images

The above descriptions of Instagram images should be coded for later analysis. Each Instagram image should be coded with multiple characteristics, including a code for the each of the major categories that you establish as important (my initial codes are derived from my Feb. 15, 2013 informal study, and are shown in the shaded column below). Using my coding, a cityscape could be coded as SM-A to indicate: Subject Matter=Cityscape. Using my coding, a “selfie” (self-portrait) could be coded SM-E(self) to indicate Subect Matter = Portrait(Selfie).

Table 2. Coding Attributes of Instagram Images and Posts

Data Analysis: Frequencies of Attributes

Once attributes of individual images are described and coded using the symbols given in Table 2, a frequency table for each attribute (such as subject matter or compositional strategy) may be constructed to find out how common an attribute is across multiple images.  For example, how common are cityscapes or sporting events? How common are dynamic diagonally composed images? How common are color images vs. black and white images?  How common are filters and apps used to modify images?  Using MS Excel, a frequency table would need to be created for each attribute that seems important. (Table 3 shown below is hypothetical, and was created in MS Word.)

Table 3. Instagram Subject Matter Frequency Table
Data Reduction

Based on analysis of about 50 Instagram images that I had collected from Tweets during a specific time on Feb 20, 2013 (see my Pinboard or Figure 1 above) , I found some trends that I have also seen in my other Instagram forays. Commonly posted subject matter included exterior and interior scenes, friends and self-portraits, food and clothing, events or sports, pets and favorite personal objects, signage, closeups, and interesting abstractions. Figure 2 below gives examples of commonly found subject matter from my Feb. 20 collection. Clearly, at the time of this snapshot in time, Instagram conveys the experiences, values, and stories of their creators through various themes and contents.  I have never been a universalist in my understanding of art forms, and I always consider art in the context of its cultural context and artists' intentions. But there's just something about these individual Instagram images that transcends their creators.

Figure 2: Subject Matter Trends from February 20 Instagram Archive

Who are all these people anyway?

Any characterization of the Instagram community has to include descriptions the Instagrammers themselves. Who are these individuals? Where are they from? How many are male/female? What other demographic data can one attribute to these Instagrammers? In my Feb. 15 study, I was able to find out quite a bit of information about the Instagrammers by following their tweets back to their Twitter and IG accounts and looking at their profiles. In some cases this also included following links to their Flickr accounts, and even to their webpages. I talked about this strategy briefly in my post about my NAEA presentation.

Some additional digging (following links back to their websites) would help in development of a separate table of characteristics of IGers.  Such a Table (see Table 4 below) would provide a "snapshot description" of these folks, and allow for coding of attributes given in each of the columns for later analysis. Additional attributes would emerge and be added in new columns, as study and analysis of these IGers commences.

Table 4. Characteristics of Instagrammers 

Neither image analysis nor describing characteristic of those Instagrammers whose images are selected would be a fast process. But using such systematic procedures such as this "snapshot in time approach" gives substance and breadth to the researcher's explanations.


Limitations of findings from this approach include the fact that we don't really what percentage of IGers (Instagrammers) also Tweet their images to Twitter, but I can say with confidence, it's a whole bunch. Other limitations include obvious questions about "which" moment in time best represents the images shared in the Instagram community, and whether or not 20 minutes is sufficient time to gather images.