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Thursday, 9 April 2015

Institutions, Procedures, Norms

One of the noteworthy aspects of the framing offered by Victor Nee and Mary Brinton of the assumptions of the new institutionalism is the very close connection they postulate between institutions and norms. (See the prior posting on this subject). So what is the connection between institutions and norms?

The idea that an institution is nothing more than a collections of norms, formal and informal, seems incomplete on its face. Institutions also depend on rules, procedures, protocols, sanctions, and habits and practices. These other social behavioral factors perhaps intersect in various ways with the workings of social norms, but they are not reducible to a set of norms. And this is to say that institutions are not reducible to a collection of norms.

Consider for example the institutions that embody the patient safety regime in a hospital. What are the constituents of the institutions through which hospitals provide for patient safety? Certainly there are norms, both formal and informal, that are deliberately inculcated and reinforced and that influence the behavior of nurses, pharmacists, technicians, and doctors. But there are also procedures -- checklists in operating rooms; training programs -- rehearsals of complex crisis activities; routinized behaviors -- "always confirm the patient's birthday before initiating a procedure"; and rules -- "physicians must disclose financial relationships with suppliers". So the institutions defining the management of patient safety are a heterogeneous mix of social factors and processes. 

A key feature of an institution, then, is the set of procedures and protocols that it embodies. In fact, we might consider a short-hand way of specifying an institution in terms of the set of procedures it specifies for behavior in stereotyped circumstances of crisis, conflict, cooperation, and mundane interactions with stakeholders. Organizations have usually created specific ways of handling typical situations: handling an intoxicated customer in a restaurant, making sure that no "wrong site" surgeries occur in an operating room, handling the flow of emergency supplies into a region when a large disaster occurs. The idea here is that the performance of the organization, and the individuals within it, will be more effective at achieving the desired goals of the organization if plans and procedures have been developed to coordinate actions in the most effective way possible. This is the purpose of an airline pilot's checklist before takeoff; it forces the pilot to go through a complete procedure that has been developed for the purpose of avoiding mistakes. Spontaneous, improvised action is sometimes unavoidable; but organizations have learned that they are more effective when they thoughtfully develop procedures for handling their high-risk activities.

This is the point at which the categories of management oversight and staff training come into play. It is one thing to have designed an effective set of procedures for handling a given complex task; but this achievement is only genuinely effective if agents within the organization in fact follow the procedures and protocols. Training is the umbrella activity that describes the processes through which the organization attempts to achieve a high level of shared knowledge about the organization's procedures. And management oversight is the umbrella activity that describes the processes of supervision and motivation through which the organization attempts to ensure that its agents follow the procedures and protocols.

In fact, one of the central findings in the area of safety research is that the specific content of the procedures of an organization that engages in high-risk activities is crucially important to the overall safety performance of the organization. Apparently small differences in procedure can have an important effect on safety. To take a fairly trivial example, the construction of a stylized vocabulary and syntax for air traffic controllers and pilots increases safety by reducing the possibility of ambiguous communications; so two air traffic systems that were identical except with respect to the issue of standardized communications protocols will be expected to have different safety records. Another key finding falls more on the "norms and culture" side of the equation; it is frequently observed that high-risk organizations need to embody a culture of safety that permeates the whole organization.

We might postulate that norms come into the story when we get to the point of asking what motivates a person to conform to the prescribed procedure or rule -- though there are several other social-behavioral mechanisms that work at this level as well (trained habits, well enforced sanctions, for example). But more fundamentally, the explanatory value of the micro-institutional analysis may come in at the level of the details of the procedures and rules in contrast to other possible embodiments -- rather than at the level of the question, what makes these procedures effective in most participants' conduct?

We might say, then, that an institution can be fully specified when we provide information about:
  • the procedures, policies, and protocols it imposes on its participants
  • the training and educational processes the institution relies on for instilling appropriate knowledge about its procedures and rules in its participants
  • the management, supervision, enforcement, and incentive mechanisms it embodies to assure a sufficient level of compliance among its participants
  • the norms of behavior that typical participants have internalized with respect to action within the institution
And the distinctive performance characteristics of the institution may derive from the specific nature of the arrangements that are described at each of these levels.

System safety is a good example to consider from the point of view of the new institutionalism. Two airlines may have significantly different safety records. And the explanation may be at any of these levels: they may have differences in formalized procedures, they may have differences in training regimes, they may have differences in management oversight effectiveness, or they may have different normative cultures at the rank-and-file level. It is a central insight of the new institutionalism that the first level may be the most important for explaining the overall safety records of the two companies, even though mechanisms may fail at any of the other levels as well. Procedural differences generally lead to significant and measurable differences in the quality of organizational results.

Source: http://understandingsociety.blogspot.ie/2009/02/institutions-procedures-norms.html

Wednesday, 25 February 2015

Count Occurrences of Factor in R

events <- data.frame(type = factor(c('A', 'A', 'B'), c('A','B','C')), quantity = c(1, 2, 1))

# Method 1
table(events$type)

# Method 2
xtabs(quantity~type, events)

# Method 3
aggregate(quantity~type, events, FUN=sum)

# Method 4
library(plyr)
ddply(events, .(type), summarise, quantity = sum(quantity), .drop=FALSE)


Thursday, 19 February 2015

Adjacency Matrix is an amazing Tool for Analysing Networks

I work a lot with adjacency matrix, a way of representing a relationship network. Adjacency matrix transfers a network graph into a well developed mathematical form. This opens the door to analysing networks using rigorous mathematical tools. The more I use it, the more useful I find this invention is.

1. In addition to indicating which nodes link to which nodes, with or without direction -- the most fundamental function, the matrix can conveniently reflect how important the links are (adding weight values to the corresponding elements).

2. Doing various elementary transformations of the adjacency matrix can achieve a variety of changes of the network, such as changing the order of the nodes, merging the relationships of two nodes.

3. One can assign attributes to nodes by multiplying the matrix (by row or column) with a vector storing the attributes.

Tuesday, 3 February 2015

Dropping Factor Levels in R

  • drop.levels {gdata} # Drop unused factor levels
  • droplevels {base} # The function droplevels is used to drop unused levels from a factor or, more commonly, from factors in a data frame.
  • When creating data frame or importing data into data frame (loading data with read.table, read.csv or the like), character vectors are converted to factors by default. To avoid this, set option (stringsAsFactors = FALSE)

Wednesday, 14 January 2015

Asking for Comments via Emails

Here are a few phrases you can use to ask colleagues for suggestions, or feedback, on a document you’ve prepared.

If you want to make sure that other members of your team are informed about the work you’ve been doing, you can use sentences like these to express interest in their opinions:

 I’d be grateful for any comments or suggestions you might have.
 I’d like to get some feedback on the report before we send it out.
 Please let me know if you’d like to propose any changes.

If you want to make a stronger request for feedback, making it clear that you expect a response from your readers, you can use sentences like these:

 Please take a look and let me know what you think of this draft.
 I’d like to receive detailed feedback on this version of the document.
 I’d appreciate it if each of you can take a few minutes to review and comment on the report.


Write an email to a group of colleagues, announcing that you have completed a business document for your company and that you would like them to read and review it before you submit it to your supervisor. Be sure to include the following points:

 The type of document you are sending
 A way to find the document (for example, as a file attached to your email)
 The type of comments you are asking for
 A deadline for submitting comments

NB: You can invent details such as the name of the company or product if you want, but it is not necessary to complete the task

  • Subject: Document for review

Dear Emily,

I should be glad if you could review the attached document. Can you please let me

know if you have any comments?

I would like to receive your feedback by 5:00pm next Wednesday, so that I can

make any changes you feel are necessary.

Thank you very much for your attention. I look forward to hearing from you.

Regards,

Sandra

  • Subject: Draft of quarterly sales report
Dear Colleagues,

I’ve just completed a draft version of our department’s sales report for the most recent quarter, which you will find attached as a Word document.

I’ve been asked to submit the final version of this report to our head office no later than 9:00am on Friday, and I’d very much like to hear your feedback on the draft before I send it out. If you have any comments or suggestions, I’ll need to receive them by 3:00pm Thursday so I can refer to them when I prepare the final version on Thursday afternoon.

I look forward to hearing from all of you.

Thanks and best regards,

Simon

Wednesday, 12 November 2014

Convert Matrix into Symmetric in R

  • require(Matrix):
forceSymmetric(dat, uplo="U"))
  • Assign the lower triangular part  to the upper triangular part:
dat[upper.tri(dat)] <- t(dat)[lower.tri(dat)]
  • micEcon package:
symMatrix(dat[upper.tri(dat, TRUE)], nrow=nrow(dat), byrow=TRUE)

Monday, 23 June 2014

Transforming NetLogo Simulated Networks into UCINET for Analysis

There's a program called NetLogo. It's an open-source agent-based modeling program. And it's awesome, although you have to spend some time with it. There are some example models that are automatically downloaded into a library when you download the program, and several of them are network simulators (they'll simulate a virus in a network, diffusion of a directed network, the formation of giant components, preferential attachment, etc).

There's a program called UCINET too. It's a social network analysis program which works with a freeware program called NETWORK which allows you to visualize networks. UCINET can only be run on Windows, and you can get a free trial you 60 days. With it, you can take a network generated in NetLogo and run all sorts of network diagnostics and alter your network image in whatever ways you like (I have yet to figure out if there is a way to keep track of the time variable somehow- perhaps as a link or turtle attribute, which could then be input as a node attribute in NETWORK).

They should probably be able to talk to each other, right? And then you could create rules for behavior in your NetLogo, simulate a network on those rules, analyze that network or a set of random simulations, and see if your rules are creating the types of networks you see in reality. That would be pretty cool, not? In the absence of knowing much about programming, here's a semi-labor intensive way to make this happen (doubtless R or some other program can do a lot of this already):

(1) In NetLogo:
File > Models Library > Networks > Preferential Attachment > Open
Select the Procedures tab
At the very top of Procedures, above the setup procedures, add "turtles-own [ my-list-partners; ]"
In the Main Procedures section, in the "to go" command, add "ask turtles [ set my-list-partners ([who] of link-neighbors) ]" just above the "tick" command
Select the Interface tab (and pray you don't see an error message)
Setup
Go until you have a network you like the size of
File > Export > World... > Save it somewhere
(there may be a more efficient way to create an output with just the variables of interest, but the below commands will work as well)

(2) In Excel:
Open the network's csv file you just created
Delete columns B:M
Delete rows 1:13
Delete rows below your initial ego/alter list (everything including and below "PATCHES")
Edit > Replace... > type in "[" into the "Find what:" space, leave "Replace with:" blank > Replace All > OK
type in "]" into the "Find what:" space, leave "Replace with:" blank > Replace All > OK > Close
Select column B (the commands below might depend on your version of Word)
Data > Text to Columns... > Delimited > Next > select "Space" as the delimiter and deselect "Tab" > Next > Finish
Hand select the frame with the data
Copy

(3) In UCINET 6
Data > Date editors > DL Editor
In the DL Editor, select the data tab
Select the first cell
Paste
Under "Data format:", select "Nodelist (1-mode)"
File > Save UCINET dataset > name it and save it somewhere
Close the DL editor
Visualize > NetDraw

(4) In NetDraw (which is automatically downloaded as part of UCINET)
File > Open > Ucinet dataset > Network
Select your file, which will end with ##h
Click OK

You can play with it from there. There's also an ability to upload attributes into NetDraw (like turtle color or breed), or resize nodes according to their degree, or any of a number of other options. If you're network in NetLogo has several components, UCINET can handle that too. I imagine there's some way to do a lot of the data reformatting/exporting/
importing automatically. You could also probably apply a similar alteration in code to other network models within NetLogo and use the same procedures to get it into UCINET.

Best of luck! Let me know if anything interesting comes of this/you find a more efficient way to accomplish the same thing.


Source: http://sexandstats.blogspot.ie/2011/09/network-analysis-transforming-netlogo.html

Thursday, 12 June 2014

Common Words in Spoken Dialogues

There are a number of words that are common in spoken dialogues that do not occur in written forms. This section discusses how such words should be transcribed. Where possible, we use the spelling from Quirk et al. (1985).

Filled Pauses Filled pauses are very common in natural dialogue. There seem to be two types, ones that sound like "uh" and ones that sound like "um". The endings of these words are often prolonged, thus tempting transcribers to label it is "ummm". Rather, these words should be classified as either "um" or "uh", and transcribed as such. We also include "er", which is more common in British accents. Note that the filled-pauses should never be transcribed as partial words.
umFilled pause.
uhFilled pause.
erFilled pause. More common in British English.

Acknowledgments

The following is a list of commonly occurring acknowledgments, and how they should be spelt.
okayAgreement. Speakers will often produce variants of this, such as "kay", "mkay", "umkay". All of these variants should be spelt as "okay".
uh-huhAgreement.
uh-hmAgreement.
mm-hmAgreement.
uh-uhDisagreement.
mmAgreement, stalling for time
huhRequest for clarification. Puzzlement.
hmStalling for time.
nahInformal version of "no".
nopeInformal version of "no".
a-haInterjection denoting surprise, as in "aha< I found it", rather than "uh-huh" as an acknowledgement ha Interjection, similar to "aha".
ohSurprise. ooh As in "ooh, that's gross."
yeahInformal version of "yes"
yepInformal version of "yes"

Contractions

Contractions, that are common, should be written as one word. The following is a list of common contraction endings. Note that there can often be an ambiguity as to whether the speaker was saying the words as one or as two individual words, especially since words are often blurred together. If in doubt, annotate the word pair as two separate words, spelling out the second in full.
'llfor "will"
'vefor "have"
n'tfor "not"
'refor "are"
'sfor "is"
All other contractions are left to the transcriber's discretion as to whether they should be transcribed as one word or two.
Word Pairs There are some word pairs that are so altered (in pronounciation) that they seem to be one lexical item. Such pairs can be transcribed as single words. Below, we give some common word pairs.
lemmefor "let me"
wannafor "want to"
gonnafor "going to"
gottafor "going to"



Extracted from PostScript by R. Paul McCarty 2001/07/30

Friday, 6 June 2014

On Paper Reading

Paper is not something you should read a large number of, but something you should read a number of times.

Rereading papers can be more useful than starting new papers, conditional on careful selection of papers to read.

A paper is good because it clearly tell you where it comes from and where it goes to, and can inspire readers with various interests.

Monday, 19 May 2014

Start to Change

I feel the situation starts to change from this week on. I will become more efficient at work gradually. Here I list the tasks to do for this week (20140519-20140525):

  • Submit the abstract by Monday;
  • Interview (QQ msgs) Li and Dad for setting up the ABM; 
  • Finalize the ABM of peer effects among smallholders;
  • Complete the statistical analysis on the simulation data;
  • Complete a first draft paper for peer effects (including all sections);
  • Start to do the daily recaps (new words, paper(s) read, being honesty, etc.);
  • Figure out how to import the map to NetLogo;
  • Email to a prof.