WRITING PAPERS AND GOING TO CONFERENCES

Gita Subrahmanyam

Authoring a PhD and Developing as a Researcher

OUTLINE OF WORKSHOP

• Why go to conferences and seminars?

• Hierarchy of conferences

• Writing, structuring and proposing papers

• Delivering papers

WHY ARE YOU HERE TODAY?

• As a table, talk about your experiences to date

• Have you been to a conference? As an attendee or as a paper-giver?

• Do you have a conference coming up that you would like help with?

• Why are you here today? What do you hope to get out of today’s workshop?

Credit:www.imageafter.com

Transmitting ideas is a key step in getting feedback and upgrading your knowledge.

WHY GO TO SEMINARS AND CONFERENCES? 1. For staff

• Create deadlines using short papers to kick-start your publications

• Meet collaborators, friends, age cohort• Plug into the wider profession and gain

an understanding of fashions, trends, tribes, taboos, discourses - and where the LSE sits

• Collate oral wisdoms, gossip, tips• Book exhibitions, meet with publishers,

network at dinners, receptions, bars

• Key socializing venues – networking • Spot potential examiners, meet key

academics and hear professional gossip• Gain valuable critiques of your work –

determine what needs to be changed or improved

• Meet others in your peer group involved in the same areas of research (future collaboration potential here)

• In USA: See how the job market works (early stages) and enter it (later stages)

WHY GO TO SEMINARS AND CONFERENCES? 2. For PhDs

HIERARCHY OF CONFERENCES

• Seminars in home institution - known audience

• Postgraduate conferences • External seminars, specialist groups in

your profession (wider audience)• UK national conference – choice of panels• European-level international conferences –

workshops, panels, specialist groups• US/global conferences – huge attendance

but often tiny audiences at individual panels – real action in bars, book fairs, receptions

THE ELEMENTS OF A GOOD PAPER AND

PROPOSAL

CONFERENCE PAPERS SHOULD BE

• Short - between 6,000 and 7,000 words• Focus on one idea or argument, not on

multiple themes – so do not try to incorporate your entire PhD into a paper

• Paper should be a good illustration of your work (e.g., not on a topic peripheral to your PhD or research expertise, in order to fit within a panel theme)

• Paper should be designed for publication and meet publication standards in terms of style of presentation and methods

FOCUS ON THE ‘NEED TO KNOW’ CRITERION

• Normal (written) form is:

– What do readers really need to know?

• Conference (presentation) form is:

– What does the audience really need to see on screen?

– What do listeners really need to have explained to them?

‘NEED TO KNOW’ IMPLICATIONS 1

• However literary your normal style, plan the talk as a sequence of exhibits

• Put all that you want to say/show on screen, in a user-friendly manner

• Practice timings for your talk

• Aim for a fast, well-paced start – do not ‘warm up’ the audience to your subject

• Sell the paper – don’t be diffident

‘NEED TO KNOW’ IMPLICATIONS 2

• Organise your talk into 3 minute chunks, planning for one display per chunk

• Use PowerPoint (not Word) to compose your displays – and have OHP backups!

• Text should be free-standing and readily understandable without you speaking (audience will deconstruct it like that)

• Try to avoid a build-up of slides or too many ‘flying bullets’ – delays exposition and too controlling

‘NEED TO KNOW’ IMPLICATIONS 3

• Pick a font that is visible to someone in the back row - like this one

• Put equations and quantitative tables into separate image screens, magnified so that the smallest subscript is visible

• Preferably use summary data tables, rather than detailed ones

• Pick the best feasible fonts for display

TIME LIMITS FOR PRESENTATIONS

• Seminars ... 30 to 40 minutes• UK and most European conferences -

20 minutes per paper, then questions; normally 2 or 3 papers per panel

• US and most international conferences - 10 to 15 minutes per paper, followed by questions; often 4 or 5 papers per panel

• Workshops and intensive conferences – 20-30 minutes per paper, followed by one-hour discussion time

IMPLICATIONS FOR PROPOSALS

• A conference proposal/abstract should be an accurate and concise summary of what the paper delivers

• Check the ‘Call for Papers’ carefully– What are the key themes of the

conference?

– What kind of presentation will you do?

– How long should the abstract be?

– When is the deadline for submission?

IMPLICATIONS FOR PROPOSALS (2)

• ‘Need to know’ criterion should guide abstract– What do organisers need to know to

assess whether to accept the paper and where to place it in a panel?

• Core argument/bottom-line findings should form centre-piece of the abstract

• Don’t waste words on literature review or methodology

HAVE A GO

• Write a proposal/abstract for the conference of your choice

• Follow the ‘Call for Papers’ guidelines in the example you brought in, EXCEPT stick to a maximum of 200 words

• If you haven’t brought a ‘Call for Papers’, then try using one of the spare copies at the front of the room

A GOOD PROPOSAL/ABSTRACT

• Sentence 1 – a hook, indication of motivation (for you and reader)

• Sentences 2 –3 – formulation of research problem/question

• Sentences 3 – 4 – outline of core finding (maybe a sideways glance at method)

• Sentences 5 – 6 - implications

GET SOME FEEDBACK

• Pass your abstract to the person on your left

• Read the abstract you have in front of you and think about what you might do to improve it

• Feed back to the person who handed you their abstract, and get feedback on your own abstract

WHAT CAN GO WRONG ON THE DAY WITH AN

OTHERWISE GOOD SEMINAR OR CONFERENCE PAPER

SCARY CONFERENCE VISION

- real life is more prosaic

BE PREPARED FOR A REALISTIC AUDIENCE SIZE

• Check the venue in advance for size and features – may indicate audience size

• Conference slots respond to multiple factors, including competition, timings etc

– so don’t regard small audiences, dribbling in late, in an over-large room, as unusual or depressing

• Alternatively beware of an over-large audience, cramped and uncomfortable in too small a room

BE PREPARED FOR POSSIBLE PRESENTATION PROBLEMS

• Presentation facilities vary unpredictably - you need to be adaptable

– Take Powerpoint slides in two storage formats (e.g. USB stick and CD).

– Email slides to seminar hosts.

– Take an OHP copy of slides

– Print readable ‘handout’ copies of slides for a realistic audience (say 25)

– Take 10-15 full paper copies, for zealots

THINGS TO AVOID, IDEALLY:- BEING INVISIBLE – by never standing up- HAVE NO VISUALS AIDS – unexciting- READING THE PAPER WORD FOR WORD

http://www.mcdonald.cam.ac.uk/McD/Seminar.jpg

THINGS TO AVOID, cont’d.USING BADLY CONSIDERED VISUALS – that are unreadable and do not project well on an OHP (or in PowerPoint)

PLAN FOR POSSIBILITY THAT YOU MAY BE ALLOCATED A

NOT-SO-IDEAL ROOM AND THINK ABOUT HOW TO ADJUST FOR IT

Credit: http://www.finearts.uvic.ca/visualarts/facilities/images/seminar/seminar-1.jpg

RANDOM UNIVERSITY ROOM – functional but depressing, no daylight, blackboard!

CREDFIT: http://www.eastwood.asn.au/images/hall15_b.jpg

SMALL ROOM HAZARDS – no OHP, no screen, table dominating the space,.. + dogs!

Credit: http://www.brc.ubc.ca/vtour/images/cell/L3_seminar1.jpg

LARGE ROOM HAZARDS – long thin room, audience obstructs each others’ view, no equipment for visual displays

http://www.ccc.ox.ac.uk/conference/images/semnarrm2.jpg

SUBTLE HAZARDS - half the audience can’t see the OHP, narrow tables, and uncomfortable seating arrangment

Credit: http://www.ruwpa.st-and.ac.uk/workshop2002/seminar%2520room3.jpg

THINGS TO AIM FOR, IDEALLYSTAND UP, and use CLEAR, VARIED SLIDES for best feasible delivery

http://www.sunyit.edu/news/academic/pictures/main.jpg

THINGS TO AIM FOR, cont’d FOR LARGE AUDIENCES (just in case)– think of the view from the back row

Credit: http://www.reidkerr.ac.uk/conference/images/ante2B.jpg

IDEAL SEMINAR ROOM – central display screen + OHP, wide tables, space for moving around, daylight or good lighting, smallish group

PRESENTING DATA poorly

INDIVIDUAL AND BLOC INCENTIVES UNDERWEIGHTED VOTING *

Patrick Dunleavy and Rolf Hoijer

LSE Public Policy Group,London School of Economics and Political Science,

Houghton Street,London, WC2A 2AE

Abstract: Pioneering work by Laver and Benoit (LB) argues that a drive by individuallegislator’s to maximize their per capita Shapley-Shubik power scores could explain theevolution of party systems in legislatures. But LB’s analysis exhibits several problems.Theoretically their utility premises are incompletely specified and would lead tosystematically irrational and short-termist behaviour by members of vote blocs.Methodologically LB focus on a complex ratio variable, whose patterning essentially dependson another largely unanalysed variable, the power index scores of whole vote blocs. LB haveno framework for economically analysing variations in power index scores across verynumerous and diverse voting situations. Empirically LB’s account radically mis-specifies thefactors conditioning blocs’ incentives or actors’ incentives. We show that: (i) they offer anexaggerated picture of the scope for defection; and (ii) their emphasis on the importance of‘dominant bloc’ status for the largest bloc is incorrect - dominance is often empirically trivialin shaping bloc scores when there are more than five blocs. Instead, the factors that doinfluence blocs’ scores are predictable, (if complex), patterns, which repeat in recognizableways across weighted voting situations, for any given threshold level. We demonstrate amethod for mapping these scores comprehensively and economically, and for analysinginfluences on the scores precisely.

Paper to the panel on ‘New Perspectives on Rights, Freedoms, and Powers’ at the EuropeanConsortium of Political Research, Annual Workshops 2003, University of Edinburgh, 28March – 2 April 2003.

START BADLY – I’ve printed my cover page in tiny font and slapped it on the OHP slide

a n a l y s i s , a n d h i s l o n e l y f a i t h i n t h e v a l u e o f o t h e r e f f e c t i v e n u m b e r i n d i c e s , f o r w h i c h t h e r e

h a s b e e n l i t t l e o r n o t a k e - u p i n t h e e x i s t i n g l i t e r a t u r e . B y c o n t r a s t w e b e l i e v e t h a t t h e w i d e r

e f f e c t i v e n u m b e r f a m i l y h a s l i t t l e t o o f f e r , a n d t h a t c o n t i n u i n g t o u s e u n m o d i f i e d N 2 i n

p a r t i c u l a r i n q u a n t i t a t i v e a p p l i c a t i o n s c a n n o t b e d e f e n d e d b e c a u s e o f t h e d e f e c t s s e t o u t

h e r e .

I n o u r v i e w a v e r a g i n g N 2 s c o r e s w i t h t h e 1 / V 1 s c o r e c r e a t e s a s i m p l e b u t u s e f u l

v a r i a n t o f t h e e f f e c t i v e n u m b e r i n d e x , N b :

T h e d a t a d e m a n d s o f e q u a t i o n ( 3 ) a r e n o g r e a t e r t h a n f o r t h e N 2 i n d e x , a n d N b a n d N 2 a r e

h i g h l y c o r r e l a t e d w i t h e a c h o t h e r . Y e t t h i s s t r a i g h t f o r w a r d m o d i f i c a t i o n h a s u s e f u l e f f e c t s .

F i g u r e 6 s h o w s t h e m i n i m u m a n d m a x i m u m f r a g m e n t a t i o n l i n e s f o r N b w i t h b e t w e e n 2 a n d

8 p a r t i e s , a n d a l s o i n c l u d e s t h e 1 / V 1 l i n e a n d t h e o v e r a l l m a x i m u m f r a g m e n t a t i o n l i n e f o r

N b ( w i t h a 1 p e r c e n t f l o o r f o r p a r t y s i z e s , a s b e f o r e ) . T h e a v e r a g i n g o f N 2 a n d 1 / V 1

c r e a t e s m u c h l e s s c u r v e d m i n i m u m f r a g m e n t a t i o n l i n e s . A n d a l t h o u g h t h e r e a r e s t i l l

t r a n s i t i o n s i n t h e i r s l o p e s a r o u n d t h e a n c h o r p o i n t s , t h e y a r e m u c h l e s s s h a r p t h a n w i t h N 2 .

T h e m a x i m u m f r a g m e n t a t i o n l i n e s f o r d i f f e r e n t r e l e v a n t n u m b e r s o f p a r t i e s a r e a l s o

c o n s i d e r a b l y s t r a i g h t e n e d o u t u n d e r N b , w i t h o u t s t r o n g l y v i s i b l e c u r v e s c l o s e t o t h e i r

t e r m i n a l a n c h o r p o i n t s . T h e o v e r a l l m a x i m u m f r a g m e n t a t i o n l i n e f o r N b i s a p p r e c i a b l y

l o w e r t h a n t h e 1 / V 12 l i n e u n d e r N 2 . I n f a c t t h e N b m a x i m u m f r a g m e n t a t i o n l i n e r u n s q u i t e

c l o s e t o b u t s l i g h t l y a b o v e t h e N 3 m a x i m u m l i n e s h o w n i n F i g u r e 1 . F o r i n s t a n c e , w i t h V 1

a t 6 0 p e r c e n t , t h e m a x i m u m N b s c o r e i s m o r e t h a n h a l f a p a r t y l e s s t h a n w i t h N 2 ; a n d a t

5 0 p e r c e n t s u p p o r t t h e N b u p p e r l i m i t i s 3 p a r t i e s , i n s t e a d o f 4 f o r N 2 . T h u s t h e N b i n d e x

d e l i v e r s m a n y o f t h e s a m e b e n e f i t s i n t e r m s o f m o r e r e a l i s t i c a l l y d e n o m i n a t e d s c o r e s a s N 3 ,

b u t i t a v o i d s N 3 ’ s s e v e r e k i n k s a r o u n d a n c h o r p o i n t s ( w h i c h i s e v i d e n t i n F i g u r e 4 ) .

T a b l e 2 s h o w s h o w t h e N 2 , N b a n d M o l i n a r m e a s u r e s b e h a v e e m p i r i c a l l y a c r o s s t h e

( 3 )

MAINTAIN CONSIS-TENCY:‘Some of you may not be able to see the subscripts here too well’

Figure 7.1: How health boards compare

Trtmnt rates/pop

Argyll & Clyde

33212.42

Ayrshire &

Arran

33200.32

Border

72331.011

Dumfries &

Galloway

31699.21

Fife

22876.55

Forth Valley

29748.33

Grampian

27681.49

Greater

Glasgow

31827.222

Highland

33855.18

Lanarkshire

23909.83

Lothian

31768.41

Orkney

21727.37

Shetland

28233.25

Tayside

50259.21

Western Isles

30840.19

1 Includes Berwick in 1997-98 only. 2. Estimates only due to data problems.

TABLES – complex, difficult to read, weak heading/title, unnecessary abbreviations, space wasted between data points

K e y : T h e h e a l t h b o a r d s a r e a s f o l l o w s : 1 A y r e & C l y d e ; 2 A y r s h i r e & A r r a n ; 3 B o r d e r ; 4 D u m f r i e s &

G a l l o w a y ; 5 F i f e ; 6 F o r t h V a l l e y ; 7 G r a m p i a n ; 8 G r e a t e r G l a s g o w ; 9 H i g h l a n d ; 1 0 L a n a r k s h i r e ; 1 1 L o t h i a n ;

1 2 O r k n e y ; 1 3 S h e t l a n d ; 1 4 T a y s i d e ; 1 5 W e s t e r n I s l e s .

F I G U R E 7 . 4 : H O W H E A L T H B O A R D S C O M P A R E

1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5

0

1 0 0 0 0

2 0 0 0 0

3 0 0 0 0

4 0 0 0 0

5 0 0 0 0

6 0 0 0 0

7 0 0 0 0

8 0 0 0 0

T r t m n t r a t e s / p o p

CHARTS – 3D design, small and thin, weak heading, no logic to arrangement of bars, labels in a legend, key details in micro font

Table 5: The extreme bloc sizes and per capita SS values in the triads, quinns and sevensareas

i. Triads areaBloc sizes Per capita SS scores

Description Blocs V1 V2 V3 V1 V2 V3 DiffBottom left cell All 26 26 25 1.28 1.28 1.33 0.05Bottom right cell 4 48 0.69 0.64

8 44 0.76 0.5714 38 26 25 0.88 1.28 1.22 0.4520 32 1.0 0.3324 28 1.2 0.1326 26 26 25 1.28 1.28 1.33 0.05

Top right cell 4 48 48 3 0.69 0.69 11.11 10.428 44 44 7 0.76 0.76 4.76 4.014 38 38 13 0.88 0.88 2.38 1.420 32 32 19 1.0 1.0 1.67 0.6724 28 28 23 1.2 1.2 1.39 0.1926 26 26 25 1.28 1.28 1.33 0.05

ii. Quinns area

Bloc sizes Per capita SS scores

Description Blocs V1 V2-V4 V5 V1 V2-V4 V5 DiffBottom left cell All 17 17 17 1.18 1.18 1.18 0Bottom right cell 6 31 0.65 0.53

8 29 17 17 0.69 1.18 1.18 0.4914 23 0.87 0.4520 17 17 17 1.18 1.18 1.18 0

Top cell 6 24 24 3 0.69 0.69 6.67 5.988 23 23 5 0.76 0.76 4.0 3.2414 20 20 11 1.0 1.0 1.82 0.1820 17 17 17 1.18 1.18 1.18 0

iii. Sevens area

Bloc sizes Per capita SS scores Description Blocs V1 V2-V4 V5-V6 V7 V1 V2-V4 V5-V6 V7 Diff.Bottom left cell All 13 13 13 13 1.10 1.10 1.10 0Bottom right cell 6 21 13 13 13 0.68 1.10 1.10 1.10 0.42

8 15 13 13 13 0.95 1.10 1.10 1.10 0.1514 13 13 13 13 1.10 1.10 1.10 1.10 0

Top cell 6 16 16 13 9 0.89 0.89 1.10 1.59 0.708 14 14 13 11 1.02 1.02 1.10 1.30 0.2814 13 13 13 13 1.10 1.10 1.10 1.10 0

VERY LARGE TABLES – multiple smudges of micro font are not ideal for presenting full regression results to a crowded room

PRESENTING DATA properly

Credit: http://www.pi1.physik.uni-stuttgart.de/Soellerhaus2002/Bilder/Soellerhaus2002-12.jpg

STRONG EXPOSITION – proper display, visible fonts, speaker visible… and using pointer for details

Formula for effective number of parties

(2)

Health boards

Treatment rates per 100,000 people

Border

723

Upper outlier

Tayside

503

Upper outlier

Highland

339

Ayrshire and Arran

332

Upper quartile

Argyll and Clyde

332

Lothian

318

Greater Glasgow

318

Dumfries and Galloway

317

Median

Western Isles

308

Forth Valley

297

Shetland

282

Grampian

277

Lower quartile

Lanarkshire

239

Fife

229

Orkney

217

Mean treatment rate

335

Figure 7.2: How Scotland’s health boards compared in treating cataracts, 1998-9 financial year

Notes:Treatment rates per 100,000 people The range is 506, and the midspread (dQ) is 55. Source: National Audit Office, 1999.

0 100 200 300 400 500 600 700

Orkney

Fife

Lanarkshire

Grampian

Shetland

Forth Valley

Western Isles

Dumfries and Galloway

Greater Glasgow

Lothian

Argyll and Clyde

Ayrshire and Arran

Highland

Tayside

Border

Cataract treatment rates per 100,000 people

Figure 1: How Scottish health boards treat cataracts, 1999-2000