FIM Global Survey on Orchestraspresentation and results

Colin Marchika, EHESSScientific direction: P.M. Menger

Introduction

A global approch

1) Multiple Correspondence Analysis (MCA) discriminating factors graphic representation

2) Hierarchical Clustering creating classes

3) Discussing the meaning of the classes

Sample description (1)

• From 231 orchestras to 105 usefull questionnaires

Geographical originEurope : 95 90,5 %

Germany 32 30,5 %UK 15 14,3 %Spain 13 12,4 %

USA 8 7,6 %Canada 5 4,8 %Australia 2 2,0 %

Date of fundationN.R. 4Pre 1900 30 29,7 %1900 – 1939 23 22,7 %1940 – 1969 25 24,8 %1970 and after 23 22,7 %

Sample description (2)

Size (in number of jobs FTE)N.R. 20Less than 70 33 38,8 %From 70 to 90 31 36,5 %Over 90 21 24,7 %

Relation to an institutionIndependent 50 47,6 %Opera house 32 30,5 %Broadcasting body 10 9,5 %others 13 12,4 %

MCA - active variables

• Variables for managing human ressources :• Wages-related variables :

•Number of wage categories•Differential in wages between soloists and tutti players•Seniority – wages increase

• Audition-related variables :•Proportion of orchestra membres on recruitment audition panels•Proportion of union representatives on recruitment audition panels•Existence of re-audition

• Organisational variables :• Working hours :

•Maximum number of working hours per day•Maximum number of working hours per month

•Extra-orchestra activities :•Autorisation for other occupationnal activities•Incentives for individual activities

MCA – axis description

3 main axes

• AXIS 1 : size of orchestras• wage increase (low vs high)• Number of hours per day, per month• Re-auditionning+ budget, box office vs funding

• AXIS 2 : personnal commitment• wage increase (very high), differentiation of the soloist•Involvment of musicians on audition panels

• AXIS 3 : commitment by salary vs commitment to the life of the orchestra

MCA – factor plan

MCA – nationalities in factor plan

Clustering : 5 classes or 3 classes

Very small orchestrassmall

Small orchestras

« old » orchestras old

Large orchestras (budget)large

Large orchestras (« hardworkers »)

Clustering : classes in factor plan

Clustering : describing the classes

1) with the help of actives MCA variables :managing human ressources & organisational variables

2)with the help of illustratives MCA variables :Size (budget, number of jobs, number of representation, institution, etc.

3) with all the others variables from the survey questionnaire :recordings, tours & travels, representation at work place, health and safety at work, etc.