Summer Workshops at the Graduate School of Social Science

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By The Graduate School of Social Sciences / Reading Time: 5 Minutes

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The Graduate School of Social Sciences (VU-GSSS) is happy to announce its upcoming summer workshops which will take place in June/July 2015. The intensive workshops focus on specialized qualitative and/or quantitative methods, and provide you with hands-on experience. Summer workshops are a great way to develop and/or strengthen your skills in between busy semesters of study and work.

And in between your hard labour you can enjoy the summer in wonderful Amsterdam.

Well, here goes a summary of the courses’ content and objectives.

  • Conducting Meta-Analyses.

     (By Prof. Brad Bushman, June 15-19, 2015)

The course aims at providing you with the essential tools to conduct high-quality meta-analysis. By the end of this course, participants: (1) will be able to formulate a topic to conduct a meta‐analysis on; (2) will be able to conduct a literature review to collect relevant studies for their topic; (3) will be able to code relevant variables from the studies they retrieve; (4) will be able to meta‐analyze the effects from the studies they retrieved; (5) will be able to interpret and write up the meta‐analytic results

During the five days of the course you will review and discuss important aspects about conducting meta-analysis research. And, most importantly, during the afternoons you will apply the techniques learned on your own project!!

  •  Programming and Analyzing in R.

     (By Dr. Wouter van Atteveldt, June 22-26, 2015)

R is a statistical toolkit that is becoming increasingly popular for more advanced analyses in the social sciences. R has a number of advantages over other toolkits such as SPSS and STATA. It is free of charge and open source, and it is very easy to write additional packages to add functionality.

The good news is, once you’ve learned to use R, you have access to a vast array of statistical methods and visualization techniques and to extremely versatile data processing and visualization techniques. R. This intensive hands‐on workshop will get you started using R on your own dataset. The course will provide you with both theory and hands-on practice. After having discussed the topics related to analysing in R, you will have the opportunity to use R on both provided data and your own project’s data. On the final day of course you will finally present the progress of your analyses and visualization in R: a great chance to receive feedbacks from your fellow colleagues and from the instructor.

  • When and How to Design Experiments.

     (By Dr. Jona Linde & Dr. Camiel Beukeboom, June 29- July 3, 2015)

This course will provide you with the tools to successfully design and use experiments in your project. Experiments are a very common tool in many fields of social science (e.g. communication science; organization science, psychology) and are becoming more common in fields where experiments used to be rare (e.g. political science). This course offers you a great chance to expand your knowledge of experiments and their tailored use in social sciences’ research.

The workshop will cover the philosophy of science behind experimental research, many examples of different types of research questions and experiments, the use of experiments in different social sciences, and practical issues for designing, conducting and reporting proper experiments.

Theory and practice will go hand in hand. You will not only be taught how to successfully design and carry out an experiment, but will also have the chance to update an existing design that can be used in your own research.

  • Interviewing Individuals and Groups.

      (By Prof. Francesca Polletta & Dr. Jacomijne Prins, July 6- 8, 2015)

Interviewing is a standard technique in social research, yet it poses numerous practical challenges. How should you decide whether to do individual or group interviews? How many interviews do you need? How should you deal with sensitive topics? How should you make sense of your data? Can the things people say in an interview setting be taken as what they really believe?

These are the main questions which you will be able to answer to after having attended the course.

During the workshop you will you will cover four main topics: 1) deciding whether to use individual or focus group interviews, 2) choosing a method and sample, 3) conducting interviews, 4) analyzing interview data and writing up findings. For a further intensive workshop on part 4, you can additionally follow the next workshop.

Whether or not you have already set up your project, this course will help you in developing the required skills for reflecting critically on the practical, ethical, and theoretical issues involved in interview‐based research

  • Collecting, Analyzing with Atlas.TI, and Publishing Qualitative Data.

    (By Prof. Barbara Risman, July 13- 15, 2015)

As a researcher you observe, make notes of you observations, interview people, sometimes take pictures, use written and electronic archives and do ethnography. The workshop is designed to equip participants with conceptual tools for analyzing qualitative (e.g., interview) data. Participants will develop hands on skills with how to analyze qualitative data using Atlas Ti by completing in‐class exercises with data provided. Finally, the third objective of this workshop is to provide skills to successfully turn qualitative analysis into manuscripts that can be submitted to journals for review.

The main focus of the course is on analyzing qualitative data once you have collected them.

During the three days of the workshop you will be practically trained on understanding the conceptual background of computer assisted qualitative analysis thru coding data and analysis. If available you can practice on your own data.

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So, what are you waiting for???  Check the Summer Workshops Manual for more information on the courses, credits, fees and timetable here.

Remember to spread the news to fellow colleagues at the VU and at other universities.

To sign up for the courses, or to ask questions and request additional information, email the VU-GSSS at graduate.school.fsw@vu.nl

In addition, there are more courses available in the Amsterdam Summer School. For instance have a look at the highly recommended course “Big Data in Society”, taught by  a number of Professors from our Faculty:

http://www.studyabroadinamsterdam.nl/en/summerschool/courses/big_data/big_data.asp

Enjoy!

Fieldwork: These tips are no tricks – Part 2

Efe Kerem SozeriBy Efe Kerem Sözeri / Reading Time: 7 Minutes

Fieldwork is sort of a dating site between the data and you. Tricking your dance partner will certainly make you fall, but knowing a few moves in advance can work well.

Previously, I wrote something about how to lose your way in the fieldwork and keep it cool; and on how your research can actually gain from such uncertainty. Despite how counter-intuitive it sounds, It takes experience to be lost, and a novice spirit to keep it cool.

Since the scientific progress is cumulative, I  offer below some fieldwork tips based on my humble experience (nanos gigantum humeris insidentes); and since it is collective, please share yours in the comments section.

  • Plan in advance, but keep your options open.

The previous post, “Field is the answer, what is the question?” is the first tip. As I said, Sometimes you find data, and sometimes data finds you. Fieldwork is sort of a dating site between the two of you. (See, you were planning to read one post, but there happens to be one more. Keep this tab open, and please come back after a brief detour.)

  • Do not work on the field, live in the field.

Before the fieldwork, we often have to choose types of informants who are expected to give the most detailed information –the key informants. We often plan the hours we work with them, schedule interviews. We organize our time and space in the field according to the expectations we had on the desk.

You shall realize, however, that unplanned encounters can be equally valuable. The doorman can know more about the networks of people in a town than the mayor. The waiter in the local restaurant can tell you more about the habits of people than the officers of the cultural planning branch. And an unemployed young man can define neoliberalism better than the books on your desk.

Having your recorder always on and your field notebook always open will not work; it can distance the daily encounters you may have. But if you keep communicating with random people in your off-work time, you may obtain new insights that you could never have planned.

  • Have your permits, but do not rely solely on them.

For a country where the state authorization is the sole source of legitimacy, be sure to have your permits with you at all times in the field. A piece of paper with a local governor’s stamp may mean nothing to you, but in a remote village when a suspicious person asks about it, that paper can win you the village.

Having said that, an official permit to research is not the best way to earn trust; the surest way to access people is to have someone from the community to introduce you.

In the Tugelaweg project, where I studied the low income families’ struggle in the housing market, knocking doors with the renovation company’s contact person turned out to be very wrong: neighbors who saw me with the company employee thought that I worked for the company, and this initially prevented my access to the people who were opposing to the project. Only after I managed to gain trust of an opposing group leader, I had an access to the rest of my sample.

In the Turkish fieldwork, where I took part in an origin-of-migration study, I noticed that the local community leaders are much more trusted than the province governors. Sweet talking with village heads opened more doors than official authorisation stamps would have. And, if I manage to convince the local Imam to announce the study in the village (from the loudspeakers of the mosque where the call for prayer -the azan- is made) then the open doors would certainly be  welcoming.

  • Mark their words: Your informants know about your results even before you think

While the results of complex logistic regression models are what counts in our papers, I actually developed the core ideas of my dissertation during my stay in a central Anatolia town for a month. It may sound surprising that the SPSS and Stata on my desk often came to the same conclusions with locals who told me about their town and its people. My analysis with thousands of respondents involved computer power, while their power in knowledge was accumulated by thousands of daily encounters.

Certainly, there are questions that a local key informant cannot answer, such as independent events that confound complex outcomes; but there are also questions that a quad-core computer cannot answer either, such as the sense-making processes of human beings with altering perceptions.

So, listen with both ears, and mark their words.

  • Enjoy the moment.

This will sound silly when you are rushing through deadlines, learning state-of-the-art statistical methods, pushing top journals and building the best CV, but…

Work to live.

Your CV may have your name on it, together with some of the good things you did, but your CV is not your whole story.

If you are best at being completely focused on collecting data in the field, and doing the best analysis possible back at your desk, you could soon be replaced with an artificial intelligence doing the best data mining possible from a remote server in China. And it will probably do it  better and cheaper than you.

But if you are not afraid to err, then do something irresistibly random, and end up reaching an unexpected conclusion; congratulations, you are human.
Carpe diem
.

________
Efe Kerem Sözeri is a Phd Candidate in the Sociology Department. His research project “Political baggage and Ideological Remittance” explores how the migration experience influences (or fails to influence) the political preferences and attitudes of Turkish labour migrants and their descendants, both in Western Europe and in Turkey. More info on his personal page

Using a cliché title or not using a cliché title: Or how to repel potential readers

camiel photoBy Camiel Beukeboom / Reading Time: 6 Minutes

Using a good title for your academic paper is very important to attract interested readers. Yet, quite often titles are uninformative and/or anything but attractive. Authors often manage to formulate a “completely ineffective title (…) that repels and puts off potential readers” apparently “to ensure that as few as possible are motivated to look beyond the title to the abstract, or the full text.” (Writing for Research, 2014). I like to focus on one excellent way to formulate a repulsive title: Namely to use the most annoying cliché title imaginable – that is, anything derived from the Shakespearean phrase “to be or not to be – that is the question”.

In order to test my disquieting suspicion how badly milked this title really is, I ran some searches in Google Scholar and Web of science. This revealed an impressive prevalence of Shakespearean titles. keep-calm-and-to-be-or-not-to-be-3 Searching Google scholar for “Or not to” in titles resulted in 12,900 hits. The same query in Web of science revealed 11,487 titles. Moreover, many titles include the “that is the question” part in the title. Google scholar gave 1,830 hits including it, and web of science gave 1,662 “that is the question” titles. I even found 1160 hits in Google scholar for titles including the whole shebang (i.e., the combination of “or not to” and “that is the question”).

Based on my rough search I will now provide you with some easy ways to also include the marvelous Shakespearean to-be-or-not-to-be phrase in your title:

1. Simply replace “be” with whatever is the topic of your paper. To give you some (recent) examples:

To date or not to date, that is the question: older single gay men’s concerns about dating. Suen, Yiu Tung (2015). Sexual And Relationship Therapy.

To reheat, or to not reheat: that is the question: The efficacy of a local reheating protocol on mechanisms of cutaneous vasodilatation. Del Pozzi, Andrew T.; Hodges, Gary J. (2015). Microvascular Research.

To pill or not to pill in GnRH antagonist cycles: that is the question! Garcia-Velasco, Juan A.; Fatemi, Human M. (2015). Reproductive Biomedicine Online.

To Drink or Not to Drink: That Is the Question. Rubin, Emanuel (2014). Alcoholism-Clinical And Experimental Research

To fractionate or not to fractionate? That is the question for the radiosurgery of hypoxic tumors. Toma-Dasu, Iuliana; Sandstrom, Helena; Barsoum, Pierre; et al. (2014) Journal Of Neurosurgery.

2. If possible you could also add your topic of investigation behind “be”:

To be or not to be… stationary? That is the question. DE Myers (1989). Mathematical Geology.

To be or not to be (challenged), that is the question: Task and ego orientations among high-ability, high-achieving adolescents. DY Dai (2000). The Journal of Experimental Education.

Optimized microphone deployment for near-field acoustic holography: To be, or not to be random, that is the question MR Bai, JH Lin, KL Liu (2010). Journal of Sound and Vibration.

To be or not to be humorous in class—That is the question. V Kothari, DS Rana, AS Khade (1993). Journal of Marketing Education.

Phytosterols: to be or not to be toxic; that is the question. G Lizard (2008). British Journal of Nutrition.

3. If the above does not fit to your topic, don’t worry. The easiest thing to do, is to just attach the to-be-or-not-to phrase to whatever is the topic of investigation. This works always, even if there is no apparent particular relevance:

The role of bone marrow biopsy in Hodgkin lymphoma staging: “To be, or not to be, that is the question”? M Hutchings (2012). Leukemia & Lymphoma.

To be, or not to be: Paradoxes in strategic public relations in Italy. C Valentini, K Sriramesh (2014). Public Relations Review.

The metabolic syndrome: To be or not to be, that is the question. PJ Grant, DK McGuire (2006). Diabetic Medicine.

To Be or Not to Be, That is the Question: Contemporary Military Operations and the Status of Captured Personnel. GS Corn, ML Smidt – Army Law (1999). HeinOnline.

To be, or not to be, that is the question: Apoptosis in human trophoblast. R Levy, DM Nelson (2000). Placenta.

To be, or not to be, that is the question: an empirical study of the WTP for an increased life expectancy at an advanced age. M Johannesson, PO Johansson (1996). Journal of Risk and Uncertainty.

And finally, if you still did not succeed. Just stick to the “to-be-or-not-to” phrase without adding anything significant. This example is particularly nice, with its frisky quotation marks around “be”.

Editorial: To “be” or not to “be”: that is the question. CT Frenette, RG Gish (2009). The American Journal of Gastroenterology

The above examples unfortunately do not cover all. The list goes on and on. For me, scrolling through the lists linked above simultaneously evoked subtle seizures of helpless laughter and a strong sense of discomfort. The lack of creativity is really disturbing. So please, please for my wellbeing, but also for your own good, take my advice and stay away from Shakespearian titles. These cliché titles do not leave a great impression about the author’s sense of creativity. Neither does it augur much about the content of the paper. I will certainly not read it and definitely not cite it. Because even before I start reading the abstract I will have turned away in aversion and vicarious shame.

Reference

Writing for Research (2014). Why do academics and PhDers carefully choose useless titles for articles and chapters?: Six ways to get it wrong, and four steps to get it right.

Camiel Beukeboom is an Assistant Professor in the department of Communication Science at VU University Amsterdam. He is also Program Director of the VU Graduate School of Social Sciences and initiator and editor of the Socializing Science PhD blog. (@camielbeukeboom)

Field is the answer, what is the question? – Part 1

Efe Kerem SozeriBy Efe Kerem Sözeri / Reading Time: 8 Minutes

Sometimes you find data, and sometimes data finds you. Fieldwork is sort of a dating site between the two of you.

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me, preparing for the respondents 😉 from upper left, clockwise: Acıpayam, Kulu, Şarkışla & Emirdağ

I am a qualitative scientist by nature, and a quantitative by nurture. It is not because I was weak at math, or hated computers; in fact, I am fascinated by both. It is rather that I prefer why questions over what questions, matters that are hard to quantify, human reason that comes before its act. Certainly, there are good qualitative research that reveals what happens where (Stepan, 1973), and good quantitative ones to explain why (Inglehart, 1977). But unless the data is conditioned in a laboratory (and even then so, see Zimbardo, 1973), it is acquired in the fieldwork where unexpected things can happen. This post is written to give you an idea of what to expect from it.

After various fieldworks for both qualitative and quantitative projects, I came to the conclusion that fieldwork comes not exactly as advertised. That is that “you collect data and come back to your desk.” Fieldwork is rather a site where you increase your chances of finding data –in comparison to your chances while sitting on your desk; and more importantly, what you find is not always the data that you planned to see on your desk. In a most self-reflexive way: Fieldwork is about finding yourself in the field.

Let me explain this in two cases:

1) The Tugelaweg Blocks

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From the booklet of Ymere’s Tugelaweg peoject: Zo wil ik hier wonen!

The most divergent case in terms of planning on the desk and encounters in the field might be the research for my master thesis in 2011. The original plan was that I would basically knock the doors of migrant families in an Amsterdam-East urban renovation project to ask about their sense of belonging to their dwellings, but I eventually came back to my desk with low income families’ struggle in coping with changing housing market conditions.

Certainly, I was very much influenced by the ‘Grounded Theory’ (Glaser & Strauss, 1967) which suggests that the researcher develops the theory in the field, instead of treating the data as an empirical test to an existing theory, and go beyond the mere task of describing the field as in an ethnography (see especially, autoethnography). I was also thinking much in qualitative forms of validity and reliability (Lincoln & Guba, 1985), and reading much about public sociology (see Burawoy’s 2004 ASA address) and engaged scholarship (Van de Ven, 2007).

Overall, I may not have been very successful in writing the study, but it certainly taught me to ‘keep my options’ during the fieldwork, be not so rigid about what I was looking for, and be a walking-talking thinker –reflecting about my objectives, my practice, and myself as the data reveals in the field.

2) The LineUp of 2000 Families

The LineUp study (Guveli et al. 2013 & 2014), which I am currently involved in for my PhD research, contrasts the above. A migration study that consists of 48978 individuals in 1992 families certainly requires quantitative tools and methods, and much careful planning –especially the sampling and the concepts, right? Well, let’s see. For a representative random sampling, the size and distribution of a population should be known, and often the fieldwork is practised in clusters to reflect that population properly, so you start at that sampling unit and continue. But what do you do when the population bureau data shows a street that does not exist yet? Or points you to a street which is full of industrial buildings?

You walk around the problem until you reach a solution.

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A theoretical guide to avoid hurdles in the fieldwork

I also took my turns in the Turkish migrant-sending towns looking for the ideological remittance –the influence of European political culture transferred to Turkey via return migrants. But I kept my eyes open for other types of remittance while walking, which is equally interesting:

Remittance: in money

 

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Newly built, huge mosques in Kulu and Şarkışla

Perhaps the most common feature of a migrant sending region is the visibility of economic remittances. In remote migrant villages, one can find palace-like houses built by the early migrants for the traditional family gatherings. However, these seasonal gatherings are only attended by a few grandchildren and remain empty for most of the year, making them obsolete investments. Most of the remittance also turn into pocket money for the left behind relatives, only enabling the local shops and cafés to stay open, but falling short of long term investments. The mosques, however, should be considered as investments for the afterlife. The newly built mosque in Kulu reportedly cost about €1m and paid entirely by migrant families’ lifelong savings.

Remittance: in culture

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Swedish Pizza in Kulu, Dutch Kapsalon in Emirdağ

Despite the popular belief on its oriental origins, and despite its widespread availability in ‘Turkse döner/pizza’ snack shops to support that, “kapsalon” was actually born in Rotterdam. Native Turkish people, living in Turkey, have not even heard about that food, there is no Turkish word for that. So, the traditional kebab place in Emirdağ town centre, photographed above (right), is actually preparing a Dutch food, exported to Belgium and remitted to Turkey by the migrants from Emirdağ who were living in Schaarbeek, Brussels. Though, one must note that its primary customers were the migrants who are used to eat kapsalon in Europe.

The Swedish Pizza in Kulu (left photograph) has a more complex story. With its thin dough, fresh tomato sauce and cheese, it certainly has Italian origins. But the history of migrant workers in Italian pizza restaurants in Stockholm is the story of how Turkish stewards made into chefs and took over the pizza business in Sweden. As for the side dishes, the indispensable “Pizzasallad” (cabbages with sour vinegar) is certainly not Italian, presumably a Swedish invent; and the “Vitlökssås” is certainly not Turkish -it is as foreign as knoflooksaus on döner to native Turks (yes, seriously, no one puts garlic sauce on a “lahmacun” in Turkey).

The remittance in both material and cultural tokens tells me the conservative nature of Turkish migrants in Europe: the lack of belonging is visible when the money earned by migrants is sent to Turkey instead of being invested in Europe; the cultural interactions are often one-way, Turks in Europe do not eat stamppot, they open döner shops instead. My walk in Turkish field did not lead me to the political remittance, there is no such street yet. Perhaps it is because the Turkish migrants do not really open their political baggages, so what happens in Europe, stays in Europe. Perhaps even that migrant Turks do not really live in Europe but rather create small-sized Turkeys to live in. But it takes a walk in Turkish towns to understand that.

Sometimes data surprises you, sometimes it takes a different look to understand; and sometimes, it is the lack of it that tells you the most.

Reference:

Burawoy, M. (2005). 2004 American Sociological Association Presidential Address: For Public Sociology*. The British journal of sociology, 56(2), 259-294.

Glaser, B. G. and Strauss, A. L. (1967). The discovery of grounded theory: strategies for qualitative research. Chicago: Aldine.

Guveli, A., Ganzeboom, H., Baykara-Krumme, H., Bayrakdar, S., Eroglu, S., Hamutci, B., Nauck, B., Platt, L., and Sozeri, E. K. (2013). 2000 Families: Migration Histories of Turks to Europe. GESIS Data Archive, Mannheim. (Data Set).

Guveli, A., Ganzeboom, H., Nauck, B., Platt, L., Baykara-Krumme, H., Eroglu, S., Spierings, N., Bayrakdar, S. and Sozeri, E. K. (2014). 2000 Families: identifying the research potential of an origins-of migration study. CReAM Discussion Paper Series CPD 35/14. Retrieved from http://www.cream-migration.org/publ_uploads/CDP_35_14.pdf

Haney, C., Banks, W. C., & Zimbardo, P. G. (1973). Study of prisoners and guards in a simulated prison. Naval Research Reviews, 9, 1–17.

Inglehart, R. (1977). The silent revolution: Changing values and political styles among Western publics. Princeton University Press.

Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA, USA: Sage Publications.

Sözeri, E. K. (2011). The Sense of Belonging and the Strategies of Dwelling among Turkish-Dutch Public Housing Residents in Amsterdam-East. Unpublished master’s thesis submitted to the Faculty of Social Sciences, VU University Amsterdam. Retrieved from http://www.academia.edu/1753970/The_sense_of_belonging_and_the_strategies_of_dwelling_among_Turkish-Dutch_public_housing_residents_in_Amsterdam-East

Stepan, A. (ed.) (1973). Authoritarian Brazil. New Haven: Yale University Press.

Van de Ven, A. H. (2007). Engaged Scholarship: A Guide for Organizational and Social Research: A Guide for Organizational and Social Research. Oxford University Press.

________
Efe Kerem Sözeri is a Phd Candidate in the Sociology Department. His research project “Political baggage and Ideological Remittance” explores how the migration experience influences (or fails to influence) the political preferences and attitudes of Turkish labour migrants and their descendants, both in Western Europe and in Turkey. More info on his personal page

Is participating in academic conferences worth the time and money?

van LeeuwenBy Anouk van Leeuwen / Reading Time: 4 minutes

Academic conferences are costly and time consuming. So, sometimes I wonder: Are they worth it? Or should I just continue to write my dissertation instead? After all, writing is time consuming, especially on days like this:

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Conferencing costs loads of time. Not only do we have to travel to the conference venue, and attend it, but we also have to prepare for it. Especially the latter takes a lot of time. In my experience, I spend at least a month working on a conference paper, and at least some days on a power point presentation or a hand-out.

Money

The reason that conferences are expensive is because they usually require us to travel. There is nothing wrong with that, of course, but travelling isn’t cheap. For instance, in the last two years I went to conferences in New York and San Francisco. Buying a ticket here (during peak season!), staying in hotel, paying the conference fee, and going out to dinner requires you to bring a bag of money.

What you get back for your time and money

In my opinion, there are at least four benefits of attending academic conferences:

  1. Preparing for your presentation will help you to structure your thoughts. After all, you usually don’t have much time (or space) to present your work. And of course, you don’t only want your story to be concise, but also clear. So, complicated theories have to be simplified and long results sections have to be cut to the bone.
  1. At the conference you are bound to get some (hopefully good) comments on your work, which will tell you how far it has developed. Is your research relevant? Are your research questions clear? And is your dataset suited for the question posed? These are general, but important questions that are often addressed. Knowing whether other scholars understand and appreciate your work will help you to determine what remains to be done.
  1. Learning what your peers are up to may stimulate your creativity and provide you with new research tools. After all, interesting new topics and innovative research methods are often presented at these conferences. Besides, knowing where your research field is headed is important as it will help you to position your own work.
  1. Getting to know peers on a more personal level is not only fun, but may also lead to new opportunities. Future cooperation, publication possibilities and even job offers may result from participating in these events.

So, the answer to my question of whether academic conferences are worth the time and money is: Yes. This is because conferencing provides you with new insights. These insights are likely to improve your work. For instance, having prepared a short presentation on your research, you may be able to write a more concise paper. Peers may suggest new theories that sharpen your insights, or methods that are more applicable to your data and research question. So, in a nutshell, conferencing helps to you to solve your academic puzzle, and to write down what is in your head. Just give it a go and find out for yourself.

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Anouk van Leeuwen is a PhD candidate in the Sociology Department. Her PhD research is on the (perceived) atmosphere of street demonstrations. The project is integrated in the international collaborative research project called ‘Caught in the act of protest: Contextualizing Contestation’ (CCC)

Doubting with the stars – why doubt is actually constructive for your project

Thijs WillemsBy Thijs Willems / Reading Time: 8 minutes

 

It is on rainy days like today that I tend to dream away and drown in memories of past summer. While the leaves are dramatically glowing red and yellow, and I slowly but surely replace the shorts and shirts in my wardrobe with shawls and sweaters, I still see beaches, sun and cocktails. This summer was a special one for me, as I had the chance to visit a symposium in Rhodes, Greece, and a summer school in Warwick, England. These two work trips were partially funded by the VU Graduate School of Social Sciences (VU-GSSS) and offered me the great opportunity to get up close and personal with my academic ‘heroes’. You can call me naïve, but I found it very intriguing to learn that these scholars you usually only refer to in the papers you write, actually are real human beings, with a face and a personality.

I noticed one common character trait while meeting my heroes in both Rhodes and Warwick that might seem unexpected for renowned academics: They doubt a lot! This observation was particularly noteworthy in light of their academic work in peer-reviewed journals, where they appear to argue with strong convinction to the highest degree. In real life, however, they seriously dare to doubt. This revelation was a bit troubling for me. For how can we claim to be ‘doing science’ if even those scholars who are cited a mere 10,000+ times tend to doubt about their concepts and theories? However, having carefully observed my heroes during these two events I had to conclude that an attitude of doubt might actually be at the very core of academic research. Related topics have already been raised, here on Socializingscience  and other popular media, as well as by scholars critically reflecting on the status of the field of management and organization studies (Alvesson & Sandberg, 2012; Hambrick, 2007). The article by Locke, Golden-Biddle and Feldman (2008) put things in perspective by discussing three strategic principles how we scholars can 1) recognize doubt, and 2) how we can use it constructively in a research project.

jjjj  Principle 1: Embrace not knowing

 We work in an environment where, in trying to get published, we are forced  to convince readers, to rationalize and legitimize our research process, and to strip away our text from any insecurity or imperfections that are in fact part and parcel of engaging in a PhD project. We thus have to unlearn how we typically respond to doubt in the first place: instead of resisting not knowing, embrace it; instead of turning away from doubt, turn towards it. In fact, doubt can be generative as long as you interpret it as a signal there is some work to do!

 

Principle 2: Nurture hunches

Hunches are unscientific. A hunch is a vague feeling or intuition about something that cannot be clearly discriminated or put into words. As such, they are of little scientific relevance or value. Although a hunch often makes no sense at this point in time, it might make a lot of sense in retrospect. Hunches sometimes constitute the beginnings of a great scientific discovery! More often than not, however, hunches are more like blind alleys. Typically, we try to avoid wasting time and, so we argue, hunches are unproductive. Blind alleys as well as great discoveries are inherent to doing research. Even Albert Einstein himself, perhaps the greatest hero of modern science, prioritized imagination over knowledge, and mistakes over success.

Principle 3: Disrupt the order

Once you know how to embrace not knowing and nurture your hunches, doubting is not automatically and potentially generative. A natural human reaction is to solve doubts and puzzles. However, this often implies that we start explaining things through rationalization, attempting to ‘box’ the problem in the categories of facts we already know or understand. In this way, puzzles or doubts rarely stimulate discoveries or stir up academic debate, as more often than not you end up with what you already knew in the first place. Order can even be disrupted on purpose, so the authors explain, in order to stimulate doubt; for example, by haphazardly rearranging your data set to foster doubt and, perhaps, come up with creative new solutions and understandings.

There you have it: three strategic principles, obviously extremely simplified, to foster doubt and to make it potentially generative. I have to admit that I myself doubted a great deal whether I should write this blog for an academic audience. I do not know if scientists are open to the non-factual. I have the hunch this blog might be an interesting read, but I do not know. But perhaps, at least I tickle the order of my audience a little bit, by showing how ‘unscientific’ doubting might in fact help our scientific work.

Good luck and lots of doubt!

kk

 

Reference:

Alvesson, M. and Sandberg, J. (2012), Has Management Studies Lost Its Way? Ideas for More Imaginative and Innovative Research. Journal of Management Studies, 50 (1), 128-152.

Hambrick, D.C., “The field of management’s devotion to theory: Too much of a good thing?”, Academy of Management Journal, 2007, 50 (6), 1346-1352.

Locke, K., Golden-Biddle, K., Feldman, M. S. (2008). Making doubt generative: Rethinking the role of doubt in the research process. Organization Science, 19(6), 907-918.

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Thijs Willems is a Phd candidate in the Organizational Science department. His research projects focuses on ‘The role of collaborative routines during disruptions in the Dutch railway system’. 

 

 

 

How a summer school made me even more confused

Arjen De WitBy Arjen de Wit / Reading Time: 4 minutes

 

As every motivated PhD I’m happy to attend conferences and courses every once in a while. Thanks to a grant from the VU-Graduate School of Social Sciences I was able to attend a four-week seminar on quantitative methods by the ICPSR Summer Program in Ann Arbor, Michigan. I hoped that this program would solve the causality issues I had in my research question. The contrary is true: it raised even more questions.

  1. You should use panel data! When using survey data it is better to study the same respondents over time in order to test whether changes in X are followed by changes in Y.This can make you a bit more certain of causal relations. So I used data from the Giving in the Netherlands Panel Study (GINPS) including 1,902 people surveyed over multiple years. In this study participants report their donations to 17 of the largest charities in the Netherlands, like World Nature Fund or the Salvation Army. From annual reports we know how much those organizations receive from different governmental subsidies. This allows me to compute how subsidies to an organization in a certain year are correlated with private donations in the following year.

But then the confusion came in. These are only 17 charities, are my results the same when I exclude one of these organizations? Can we expect effects to be the same for international aid organizations as for charities working in the field of health care?

  1. You should include fixed effects! Fixed effects account for variables that don’t change over time, which allows you to look only at the effect of variables that do change over time. For example, some organizations receive both more subsidies and more donations just because they are bigger organizations. An analysis that includes fixed effects for organizations rules out the effect of organization size.

But there is the confusion again. Should I use fixed effects for individuals or for organizations? A person’s gender or other individual characteristics can disturb the effect, as well as an organization’s size, sector or age. Or should I use fixed effects for each unique combination of individual and organization?

  1. You should do Tobit regression! Because most people don’t donate to all 17 organizations in the sample there are a lot of cases scoring 0 on the dependent variable. Linear regression is not appropriate in that case. Tobit regression, I was told, includes both the likelihood of scoring higher than 0 and the linear distribution of valid donations in one estimation.

Confusion! Are the decision whether or not you donate and the decision on how much you donate the same thing? Are non-donors motivated by the same considerations as donors?

  1. You shouldn’t do Tobit with fixed effects! The ‘incidental parameters problem’ means that fixed effects can make the estimation of a binary outcome variable (donating or not donating) biased. In other words, Tobit and fixed effects are not always good friends.

So shouldn’t I use Tobit? Or shouldn’t I do fixed effects? Or is there another way to account for this problem?

I went to the ICPSR summer school to get answers on the causality issues I had with my research question. Do higher government subsidies lead to lower charitable donations, is it the other way around, or is there another variable that causes both subsidies and donations? The summer school provided answers but those answers confused me even further. More difficult methods come with more difficult problems, and that’s how researchers keep on struggling with their analyses until they come up with answers that are the best they can get to.
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Arjen de Wit is a PhD candidate at the Center for Philanthropic Studies, where his research concerns the question to what extent government support affects volunteering and charitable giving. He also works for ProDemos, House for Democracy and the Rule of Law, and writes for his personal blog www.arjendewit.nl.