Soumya Banerjee
email: neel.soumya@gmail.com

Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals Novel Patterns

Scientific collaboration networks are an important component of scientific output and contribute significantly to expanding our knowledge and to the economy and gross domestic product of nations. Here we examine a dataset from the Mendeley scientific collaboration network. We analyze this data using a combination of machine learning techniques and dynamical models. We find interesting clusters of countries with different characteristics of collaboration. Some of these clusters are dominated by developed countries that have higher number of self connections compared with connections to other countries. Another cluster is dominated by impoverished nations that have mostly connections and collaborations with other countries but fewer self connections. We also propose a complex systems dynamical model that explains these characteristics. Our model explains how the scientific collaboration networks of impoverished and developing nations change over time. We also find interesting patterns in the behaviour of countries that may reflect past foreign policies and contemporary geopolitics. Our model and analysis gives insights and guidelines into how scientific development of developing countries can be guided. This is intimately related to fostering economic development of impoverished nations and creating a richer and more prosperous society.

Introduction

Scientific collaboration networks are an important component of scientific output and contribute significantly to expanding our knowledge and contribute to gross domestic product. Collaboration networks have been modelled before [START_REF] Newman | The structure of scientific collaboration networks[END_REF]2]. Here we examine a novel dataset for the Mendeley collaboration network [START_REF][END_REF]: we find novel clusters of countries with different characteristics of collaboration. We propose a dynamical model that explains these characteristics. We also find interesting patterns in the behaviour of the countries that may reflect foreign policies and contemporary geopolitics.

Collaboration Data

We use a planetary scale collaboration data freely available for download from Mendeley Labs [START_REF][END_REF]. Analysis of this data with k-means clustering reveals the following patterns: a) We plot the percentage of external connections that each country has vs. the distinct number of countries each country is connected with. The plot shown below (Fig. 1) has a distinctive shape. Each point on the plot is a distinct country. c) There are no countries with high share and high distinct number of countries connected with. Countries with a larger share of foreign connections and less distinct countries connected with are less developed nations.

d) The country with the highest number of distinct number of countries connected with and largest share of external connections is the UK (top rightmost in the plot).

d) The country with the lowest number of distinct number of countries connected with and lowest share of external connections is Algeria (bottom leftmost in the plot).

In order to explain these patterns, we propose a dynamical model for how the links are actually formed; for example poor countries might preferentially seek out collaborations with richer countries or richer countries might help disadvantaged nations (e.g. Liberia has 100% external connections). We simulate the time evolution of connections. Our dynamical model correctly predicts the broad observations of scientific connections of countries.

Mathematical Model

Our dynamical model has two compartments: developing countries (x) and developed countries (y). Developing countries grow their scientific expertise and selfconnections at a rate proportional to α*x (self-growth) and also by interacting with developed nations at a rate proportional to β*x*y. Developed nations (y) are assumed to have reached equilibrium of growth. The model, represented as differential equations is shown below:

Shown below (Fig. 2) is a simulation of how scientific connections of developing countries evolve over time for a chosen set of parameters.

For the same set of parameters we also simulated how the percentage of foreign connections should vary (over time) with the number of self-connections (Fig. 3). This plot accurately recapitulates the patterns in the empirical data (Fig. 1). It shows there are only 3 quadrants. It is consistent with and effectively recapitulates empirical data.

`Fig. 2. Simulated plot of how scientific connections of developing countries evolve over time.

Data and Statistical Methodology

All data is freely available from Mendeley Labs [START_REF][END_REF]. The table of the complete collaboration network is available for download [START_REF][END_REF]. The data was curated by Mendeley and a connection is defined as co-membership of two researchers in a Mendeley group. Further details of data pre-processing are available online [START_REF][END_REF].

All statistical analysis was conducted in MATLAB.

Discussion

We find novel patterns in the planetary scale collaboration dataset (Fig. 1). The table of the complete collaboration network is available for download [START_REF][END_REF]. We note some interesting patterns in the data:

1) The UK has a very high percentage of foreign connections; this maybe because of its colonial past.

2) Less developed or poorer countries usually have a very high percentage of foreign connections.

3) Iran has a large number of foreign connections; it is interesting that this is so despite foreign sanctions imposed against it.

4) The largest or richest countries have more distinct foreign connections. This may suggest that the rest of the world wants to collaborate and form connections with others; this could also be driven by interest in issues relevant to poorer countries like tropical diseases, socio-economic research into poverty and archaeological research in countries in Africa.

5) India has more foreign connections than China.

6) The US has a lower percentage of foreign connections but in absolute numbers it has the highest number of connections.

7) The highest percentage of foreign connections is usually occupied by very poor countries (presumably they are trying to build capability in science and technology by collaboration), e.g. Liberia has 100% foreign connections.

8) Among the developed nations, the UK has the largest percentage of foreign connections (probably reflecting its colonial heritage) 9) Some countries like El Salvador have a low percentage of foreign connections (this could be as a result of the fact that the country was embroiled in civil war for a long time). The policy implications are that it shows a need for targeted relief at starting active science and research programs in these nations. 10) South Korea, Japan, Taiwan, Japan, Germany have a low percentage of foreign connections (they have a large number of absolute connections and it is possible that they have invested very heavily in their own science programs). This is interesting since these are highly developed countries.

11) Liberia has 100% external connections: this suggests that more efforts need to be taken to develop its own scientific infrastructure.

12) Cuba has very few connections (this is again possibly due to sanctions imposed against it).

In summary we propose a dynamical model that explains current trends of clustering in scientific collaboration network. Taken together our data and models show signatures of past and contemporary foreign policies and geopolitics on the scientific collaboration landscape.

Our analysis also points to the power and generality of dynamical systems in modelling diverse sociological systems [START_REF]Competitive dynamics between criminals and law enforcement explains the super-linear scaling of crime in cities[END_REF][START_REF]A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation[END_REF].

Our model and analysis gives insights and guidelines into how scientific development of developing countries can be guided. This is intimately related to fostering economic development of impoverished nations and creating a richer and more prosperous society.

Scientific Validation

This paper has been unanimously validated in a collaborative review mode with the following reviewers:

1) Maria Jose Jorente, Universidade Estadual Paulista 2) Mariana Cantisani, Federal University of Paraíba

Fig. 1 .

 1 Fig. 1. Plot of the percentage of external connections that each country has vs. the distinct number of countries each country is connected with. Clustering is done with k-means and shows three distinct clusters.

Fig. 3 .

 3 Fig. 3. Simulated plot of self connections vs. percentage of foreign connections.


Soumya Banerjee

Joshua P Hecker
email: jhecker@cs.unm.edu

A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing

In this research we use a decentralized computing approach to allocate and schedule tasks on a massively distributed grid. Using emergent properties of multi-agent systems, the algorithm dynamically creates and dissociates clusters to serve the changing resource demands of a global task queue. The algorithm is compared to a standard first-in first-out (FIFO) scheduling algorithm. Experiments done on a simulator show that the distributed resource allocation protocol (dRAP) algorithm outperforms the FIFO scheduling algorithm on time to empty queue, average waiting time and CPU utilization. Such a decentralized computing approach holds promise for massively distributed processing scenarios like SETI@home and Google MapReduce.

Introduction

Recent years have seen a trend in moving large computational tasks to collections of inexpensive, commercial off-the-shelf (COTS) computers that are geographically distributed. This has contributed significantly to the advancement of science by providing access to large-scale shared computing resources on which to solve computationally expensive problems. Some common examples are SETI@home [?] which runs tasks on millions of computers worldwide and Google MapReduce [?] which distributes calculation of web crawled metrics among thousands of computers. This move towards distributed computing has created a need for efficient task allocation and scheduling algorithms. Such algorithms should be very scalable since these systems typically have thousands to millions of computers. They should also be robust to single-point failures and be adaptive to task demand. Recent research on grid resource allocation has focused on volunteer resource allocation, agreement-based resource allocation and economic resource allocation [?]. Multi-agent decentralized systems offer an exciting approach to distributed resource allocation. They have emergent global properties which arise from local interactions and have been previously used to model biological phenomena [?,?,?,?,?,?,?,?] and solve real-world problems [?,?,?,?,?].

Here we use such a decentralized computing approach to allocate and schedule tasks on a grid. The remainder of the paper is organized as follows: Section 3 formalizes the problems and states the assumptions, Section 4 briefly reviews decentralized computing and the advantages it can afford to a distributed allocation problem, Section 5 introduces multi-agent systems, Section 6 introduces the simulator used for the experiments in this paper, Section 7 discusses the dRAP algorithm, Section 8 deals with analysis of the cost of searching through the global queue, Section 9 discusses some dRAP optimization techniques influenced by the immune system, Section 10 deals with experiments and results, Section 11 discusses related work in this area and Section 12 presents concluding remarks and outlines future work.

Statement of Problem and Assumptions

Assume there is a queue Q of processes waiting to be allocated to processors. Each process is required to declare a priori its resource requirements viz. the number of threads into which it can be parallelized (T H n ) and the number of system resources it requires (the number of CPUs is assumed to be equal to the number of threads which can be run in parallel, CP U req ). Our system departs from traditional resource allocation techniques in that there is no centralized dispatcher. Instead, we dynamically organize a system of geographically distributed computers into clusters to service each process in Q. Over time, clusters of computers are dynamically created, dissociated and created again in order to serve the resource requirements of the processes in Q. We define a cluster as a network of computers which together can completely service the resource requirements of a single process. Clusters of computers are created so as to be proximal to each other in order to reduce latency and communication costs.

We acknowledge the following assumptions in our system:

1. Distributed computers can communicate with each other.

2. There are advantages to computing with geographically proximal computers due to network latency and bandwidth limitations. 3. A new process P 1 that comes in the system will declare a priori the number of threads that it can be parallelized into and its resource requirements (e.g. the number of CPUs it will require, I/O devices required, amount of memory, etc). 4. The approach will become viable in the asymptotic region of millions or billions of geographically dispersed computers, when there will be expected benefits from a decentralized computing approach that exploits geographical proximity and reduces latency costs, as opposed to a centralized monitor.

The extreme size of the computing grid and an ever-increasing demand for computational power places exacting demands on any scheduling, allocation and load-balancing algorithm. Here we argue that a decentralized computing paradigm presents an ideal solution to the bottlenecks and single-point failures inherent to a centralized monitor tasked with allocating resources and balancing loads in the grid:

1. The workload assigned to a centralized monitor increases as computers are added to the computing grid. A decentralized approach can alleviate the computing load on monitors. In this approach, each individual computer, or cluster of computers, will do some computation. 2. A centralized monitor makes the system susceptible to single-point failures.

Distributing load balancing and resource allocation tasks to individual computers will increase system robustness. 3. Individual computing nodes are naturally aware of their own workloads. As a result, the decentralized paradigm can achieve application-level resource management with significantly less communication overhead than a centralized monitor. 4. A decentralized system uses peer-to-peer networking to scale communication as the system grows, whereas a centralized monitor has to communicate with an increasing number nodes. 5. A decentralized system is more robust to single node disruptions and failures, whether malicious or benign. 6. A decentralized system may be able to better respond to fluctuations in process requirements e.g. in a scenario where the scheduler has to "forget" past process requirements and completely rebuild new clusters after servicing one process i.e. there is no locality in process requirements.

Multi-Agent Systems

Multi-agent systems use distributed agents to either model or solve a problem. An agent is an entity which matches some real-world object. It could be a biological cell, a virus particle, an ant or in our case an individual computer. A computer program encodes simple rules or behaviors for interacting with other agents. The agents move about in space and interact with other agents in their neighborhood according to the encoded rules. Thus the behavior of low-level entities is specified and high-level behaviors evolve as simulation time progresses. Multi-agent systems emphasize local interactions based on first principles, and these interactions give rise to the complex high-level emergent properties of interest. Such systems have been used to model biological phenomenon such as the human immune system [?], as well as solve real-world problems like communication between distributed radar transmitters [?] and efficient resource collection in swarms of foraging robots [?,?,?,?].

There is no centralized dispatcher to facilitate the formation and dissociation of clusters in the proposed dRAP algorithm. Instead, the algorithm relies on the self-emergent properties of a multi-agent system. A multi-agent or agent-based system is an architecture in which the global properties of the system emerge from local interactions.

The concept of a decentralized system presents a powerful counterpoint to the more common centralized control model often seen in business, government, and military organizations. Decentralization provides a number of important advantages over closed systems, such as robustness, adaptability, flexibility, innovation, and distributed intelligence. The key to this compelling architecture is the impressive ability of a decentralized system to react, mutate, or grow in response to challenging situations.

In any such decentralized system, the agent represents the base unit of computing power for the system. It behaves according to very simple rules. At each unit of model time (or time step), the agent senses its immediate local environment and takes actions based on its encoded rules. One rule might instruct the agent to divide if the number of neighbors is greater than 3, while another would cause it to die and be removed from the simulation if the number of neighbors is less than 2. These two examples are rules in the "Game of Life" [?], a paradigmatic system where complex patterns arise from local interactions and simple rules.

If we recast each agent's local sensing functionality as a peer-to-peer communication protocol with other nearby agents, then we can define a new set of rules for each agent that induce actions based on the state of these other, neighboring agents. Using this localized communication scheme, such rule-action pairs can be viewed as instructions for individual agents that produce decentralized computation across the system. There is no centralized monitor and yet this system is capable of performing complex computations. In fact, the computational power of such a system of distributed agents acting on simple rules has been proven to be Turing-complete [?].

We use such an agent-based system to dynamically create and dissociate clusters based on the resource requirements of each process. A snapshot of this system is shown in Figures ?? and ??.

Software Platform

For this project we utilize the multi-agent simulation toolkit MASON [?]. MA-SON consists of a fairly small and portable set of Java library files that provide for design of both model (the "algorithm" component) and visualization (the "graphical user interface" component).

The agent, the base component of computation in MASON (as in any multiagent system), is coded in the familiar object-oriented programming format: the class "Agent" that contains all generalized methods and parameters needed for the object "agent" that is simply an instantiation of the Agent class. Following this format, each instantiated agent may contain a unique set of parameters, thereby allowing for minor variation in the replicated objects.

Agents are allowed to make decisions (and even communicate with one another) in a randomized batch lock-step. That is, the MASON scheduler moves through the (randomized) queue of all agents at each time step of the simulation. Scheduling of agents continues as long as the simulation itself is running, although the user may interrupt at any point by pausing or stopping the model.

MASON in particular was selected because of its all-in-one toolkit approach, making multi-agent simulation much easier than if done from scratch, as well as the authors' familiarity and experience with the MASON system.

dRAP Algorithm

The distributed resource allocation protocol (dRAP) is described below and some intended optimizations are suggested for future work. An agent in our system is simply a computer. Each agent has a vector containing the time remaining to finish executing its current process (time rem ) and the number of CPUs in its current cluster (CP U cluster ). Each agent (or node) is guaranteed to be in exactly 1 of 4 modes (or states) during the simulation: Mode 1: An agent/node that is currently not part of a cluster and has no task assigned to it 1. The agent scans the queue Q, considers the resource requirements CP U req of unallocated tasks, and takes on the task which minimizes the equation |CP U req -1|. Mode 2: An agent/node that is currently not part of a cluster and has a task assigned to it 1. The agent continues executing the task and updates its information vector (time rem , CP U cluster ).

2. If the task requirements are not completely satisfied (i.e. if CP U req > 1), the agent will query its neighbors and attempt to form a cluster such that CP U req = CP U cluster 3. When the agent finishes executing the task, it returns to Mode 1. Mode 3: An agent/node that is currently part of a cluster and has no task assigned to it 1. The agent scans the queue Q, considers the unallocated tasks, and takes on the task which minimizes the equation |CP U req -CP U cluster | Mode 4: An agent/node that is currently part of a cluster and has a task assigned to it 1. The agent continues executing the task and updates its information vector (time rem , CP U cluster ) 2. When the task completes, the agent dissociates from the cluster and returns to Mode 1.

A key feature of our algorithm is that nodes query their neighbors (other nodes that are close to them physically) in order to form clusters. This has the effect of reducing latency and communication costs. One optimization to consider would be to delay cluster dissociation in Mode 4. This would lead to learning or memory in the system where the scheduler would be able to remember past process requirements.

Analysis of Queue Cost

The dRAP algorithm requires a traversal through the global task queue in Mode 1 and Mode 3. The algorithmic complexity is given by (n -i)m = O(n 2 m) where m = the number of tasks in the global task queue, and n = the average number of clusters. At a given timestep, the worst case can be approximated as O(nm).

Optimizations Inspired by the Immune System

The immune system is able to find rare spatially localized pathogens and eliminate them in a timely manner [?,?]. Similar to how in our system clusters of computers find processes, the immune system uses specialized cells to find pathogens in anatomical regions called lymph nodes. In previous work we showed how a sobmodular arrangement of lymph nodes could lead to fast elimination of pathogens in the immune system and also faster search for solutions in immune inspired distributed systems of computers [?,?,?]. Let an artificial lymph node be composed of a number of clusters and a process queue. Also let there be a number of such artificial lymph nodes that have the capability of communicating with each other. An 'artificial lymph node' is supposed to be a computer in charge of a number of clusters. This computer will store the process queue and also will have some memory and CPU to communicate with other 'lymph nodes'

We are interested in making the system sub-modular so that we can minimize the total time to find a cluster. There is a tradeoff between the local cost and the global cost; The local cost is O(n 2 ) and the global cost O(N/n). The total cost of traversing through the queue in a lymph node and the cost of communicating with other lymph nodes can be summed up as :

t total = t local + t global (1)
t total = O(n 2 ) + O(N/n) (2)
where where n is the number of clusters in a single lymph node and N is the total number of clusters in the complete system. We assume that the global cost of finding another cluster in another lymph node that can service some process requirement is proportional to the number of lymph nodes (where N/n is the number of lymph nodes in the system).

Minimizing the total time cost, we get 2n -N/n 2 = 0

n = O(N 1/3 ) (3)
This implies that in larger systems (more computers. more clusters and more lymph nodes), the number of clusters within a single lymph node should grow larger but only sublinearly in the number of total clusters in the system. This would balance local costs of queue traversal and global costs of finding another lymph node with another cluster that can service the process. The key point here is that the number of clusters in a lymph node should scale sub-linearly with the size of the whole system, i.e. if a system of networked artificial lymph nodes were to grow a 1000 times bigger (1000 times more clusters), then the number of clusters within a lymph node need only increase by a factor of 10. Such submodular systems inspired by the immune system have been proposed previously for mobile ad-hoc networks, control of mobile robots, intrusion detection systems and peer-to-peer networks [?,?,?].

More generally, if the local and global communication costs scale with exponents α and β, we have

t total = O(n α ) + O(N γ /n β ) (4)
Minimizing the expression with respect to N , we get

n = O(N γ α+β ) (5)
1. If γ < α + β we have sub-linear scaling. We conduct several experiments that compare our dRAP algorithm to a null model, i.e. a first-in first-out (FIFO) scheduling system. Additionally, we measure the effective computational complexity of queue traversals and examine the scaling properties of our system by varying the number of nodes and measuring the effect on performance. We define two timing metrics on which our system performance will be judged: T complete is the time required to complete all tasks in the queue, and T wait is the average wait time for a task added to the queue. Unless otherwise noted, system parameters are defined as such: number of nodes = 100, number of tasks = 1000, tasks are randomly selected from a normal distribution s.t. CP U req varies from 1 to 5, with initial time rem varying from 25 to 125 in increments of 25. That is, a task t i with CP U req = 1 has an initial time rem = 25, and a task t j with CP U req = 5 has an initial time rem = 125. All averages are computed across 10 trials.

Comparison to Null Model

Here we present three separate experiments which compare the dRAP and FIFO algorithms. The first is a simple timing comparison that looks at T complete and T wait for each case. Values are presented in Table ?? (including 95% confidence intervals). We observe an approximate 20% reduction in T complete and an approximate 25% reduction in T wait when comparing dRAP to FIFO.

Our second experiment comparing dRAP and FIFO involves average cluster utilization. Because dRAP assigns tasks s.t. CP U cluster == CP U req , this ensures that all nodes in the cluster will be utilized. However, the FIFO scheduling system hands out tasks to the first available cluster, meaning it allows for the possibility that CP U cluster > CP U req . For example, a task with CP U req = 2 that is assigned to a cluster with CP U cluster = 5 will leave 3 unused nodes. Thus, we present an analysis of cluster utilization using the metric in Equation ??:

µ cluster = CP U req CP U cluster (6)
µ cluster dRAP 100% FIFO 56% (54%,58%) Table 2. Average cluster utilization of dRAP and FIFO scheduling algorithms with 95% confidence intervals If CP U cluster ≤ CP U req , we simply set µ cluster = 1. Values are presented as percentages in Table ?? (note that dRAP's µ cluster is always 100% by definition).

Finally, our third experiment is designed to measure global node utilization over the time of the simulation. Here we simply document the number of nodes that do computation on a given timestep and normalize by the total number of nodes in the system. Results are displayed in Figure ?? (taken from a single simulation run). We observe that the dRAP algorithm utilizes approximately 90-95% of the nodes for the majority of the simulation, while FIFO utilizes approximately 70-75%.

Effective Complexity

For this experiment, we estimate the "effective" computational complexity of the dRAP algorithm. That is, in comparison to the qualitative O(nm) worst case runtime per timestep, we are interested in how much of the task queue must be traversed in order to properly fit the CP U cluster == CP U req requirement. Total tasks traversed per timestep from one selected simulation run are presented in Figure ??. Note that the initial traversal (timestep "0"), although difficult to see, is approximately 11,000. "Worse case" here, as addressed above, is O(nm), or 100, 000 tasks traversed per timestep if n = number of clusters = number of nodes = 100 and m = number of tasks = 1000. From this plot (plus additional runs not included here), we can conclude that effective computational complexity is no more than approximately 10% of the worst case runtime O(nm).

Scaling

For our last experiment, we are interested in collecting information on the scaling ability of our algorithm. Our goal in this test is to increase the number of nodes (in intervals of 50), while also maintaining an equal number of neighbors for each node. That is, we ensure that the neighborhood size parameter defined in the simulation scales inversely with the number of nodes s.t. a given node has approximately the same number of neighbors regardless of the total nodes in the system. Results are presented for our two timing metrics: T complete scaling in Figure ?? and T wait scaling in Figure ??. Data in both figures are log 2transformed in order to correlate doubling of nodes with halving of the timing metrics.

We note a near-perfect scaling for both timing metrics, as shown in the fitted power law equations inset into each plot (Figures ?? and ??). Note that the T wait exponent above 1 is most likely a result of inexact tuning of the neighborhood size with increasing nodes, and this issue will rectified in future work. Resource allocation for grid computing is an active area of research. For example, SLURM [?] is a configurable Linux utility for cluster allocation that uses static allocation of nodes to clusters, called partitions, in contrast to the dynamic cluster allocation presented in this paper. LSF [?] is another proprietary cluster management facility, however details of its allocation algorithm are not publicly available.

12 Conclusions and Future Work

In this paper we have presented an algorithm for allocating, scheduling and loadbalancing processes on a massively distributed system. This is very relevant to current research in operating systems, especially with a trend of moving computation tasks onto inexpensive, distributed hardware. The proposed decentralized algorithm draws inspiration from biology, adaptively creating and dissociating clusters from nodes to match task demand. Decentralization enables scalability, robustness, alleviation of computing load on monitor, better response and adaptability to process queue fluctuations and learning about process requirements. The dRAP algorithm outperforms a FIFO scheduling algorithm on time to complete all tasks, average waiting time and CPU utilization. The scheduling is also shown to be robust to a malicious adversary that might permute the order of the tasks such that high demand tasks would be queued first followed by low demand tasks. A key feature of our procedure is that nodes communicate with neighboring computers in order to dynamically form clusters. Hence our algorithm also holds promise in areas where it is advantageous to communicate with immediate neighbors due to network latency, e.g. Google MapReduce uses a locality optimization to reduce latency due to network communication [?]. The comparison of this algorithm to other scheduling algorithms like SRTF (Shortest Remaining Time First) on other metrics like response time, as well as collection of data on the exact distribution of process demand in a queue in a real-world scenario, will be the subject of future investigation.

Acknowledgements

We thank Dr. Dorian Arnold for fruitful discussions.

Scientific Validation

This paper has been unanimously validated in a collaborative review mode with the following reviewers:

-Cyrille Bertelle, from Universit du Havre (France) -Pierre Collet, from Strasbourg University -Carlos Jaime Barrios Hernandez

Fig. 1 .

 1 Fig. 1. Agents in large clusters; 1 free agent

2 .

 2 If γ > α + β we have super-linear scaling. 3. If γ = α + β we have linear scaling. 4. If γ/(α + β) = 0 we have no scaling (constant). 5. If γ/(α + β) < 0 we have negative scaling.

Fig. 3 .

 3 Fig. 3. Global utilization of nodes throughout simulation

Fig. 4 .

 4 Fig. 4. Total task traversals by all clusters per timestep.

Fig. 5 .Fig. 6 .

 56 Fig. 5. Scaling of T complete

Table 1 .

 1 Average timing comparison of dRAP and FIFO scheduling algorithms with 95% confidence intervals.

	T complete	Twait
	dRAP 845.60 (861.94,829.26) 342.54 (349.30,335.78)
	FIFO 1071.20 (1088.99,1053.41) 475.31 (485.79,464.82)


Laure Neumayer

Symbolic policies versus European reconciliation: the Hungarian 'Status Law'

Since the end of the Cold War, painful historical events that could not be openly discussed during Communism have become more salient in public debates throughout Central and Eastern Europe. The border changes and forced population transfers that occurred after the First and the Second World War, and more specifically the plight of the civilians who experienced these traumatic events, have been one of the most contentious issues discussed in the new democratic regimes. The enduring tensions surrounding the situation of the Hungarian minorities are another striking example of the contemporary political consequences of these 'wounded histories'. The redrawing of Hungary's borders in the wake of the dissolution of the Austro-Hungarian monarchy, which resulted in the loss of a large part of its former territory and population i , is still portrayed as a 'historical injustice' by some parts of the Hungarian society and political leaders. This perception justifies 'symbolic policies' aimed at reinforcing the link with the diaspora, as was made clear as early as 1989 when the Hungarian Constitution was amended to include the following statement of support: 'the Republic of Hungary bears a sense of responsibility for the fate of Hungarians living outside its border and shall promote and foster their relations with Hungary'.

Because of Hungary's history of irredentism and the ambiguous statement of some of its politicians ii , the situation of the Hungarian minorities has been closely monitored by European organizations since the early 1990s. The main concern of the European Union (EU), the Council of Europe (COE) and the Organization for Security and Cooperation in Europe (OSCE) was originally to stabilize the former Soviet bloc through the diffusion of democratic standards. In the late 1990s, these organizations developed a more ambitious policy aimed at 'reconciling' former adversaries by helping them to 'settle accounts with the past' and to deal with contested memories. Yet national symbolic policies

repeatedly conflicted with European 'reconciliation policies' (Neumayer, 2007b). This chapter presents a case study of such an intervention in a history-rooted conflict, framed as an issue of national minority protection, which opposed Hungary to some of its neighbors (mainly Slovakia and Romania) between 2001 and 2003. The controversy started when the Hungarian parliament passed the Act LXII of 2001 on Hungarians living in Neighboring States, often referred to as 'Status Law' from an earlier draft's title, designed to assist Hungarian minorities. After two years of fierce diplomatic debates, a watered down version of this piece of legislation finally entered into force, only to become void when the neighboring states joined the EU. iii Interestingly, this diplomatic conflict quickly reached the European level of government: the Parliamentary Assembly of the COE asked its advisory legal body to assess the conformity of the 'Status Law' with international legal norms. Simultaneously, the OSCE was monitoring the situation and providing its own analysis of the conflict. The EU, in contrast, tried to minimize its involvement in a dispute between three future member states over matters which were not part of the acquis communautaire, by deferring to the COE's legal analysis and calling upon the conflicting parties to find a modus vivendi in the name of reconciliation. iv The existing literature on the 'conditionality' imposed by the EU on the CEE candidate countries prior to its enlargement has shown that the case of minority protection was very specific in two respects.

First, the acquis communautaire was non-existent in that field when the EU decided to enlarge, and the standards which have been 'exported' to Central and Eastern Europe in the 1990s actually originate in the COE and the OSCE. Second, there is no consensus among Western European countries as regards the definition of national minorities and the legitimacy of their 'protection' through individual or collective rights [START_REF] Hughes | Monitoring the Monitors: EU Enlargement Conditionality and Minority Protection in the CEECs[END_REF]. That is the reason why European agencies provided an ad hoc expertise that combined diplomacy and law through the promotion of 'good neighborly policy', intergovernmental dialogue and regional cooperation. This chapter argues, however, that these elements alone do not allow for a complete picture of the way European organizations tried to solve the Status Law dispute. It is suggested here that cross-references between the COE and the OSCE played a crucial role in the consolidation of notions and categories of analysis which are tenuous from a strictly legal point of view, such as 'kin-minority', 'kin-state' and 'home-state'. The standards promoted by European organizations remained inherently vague: they allowed for a short-term solution to the dispute but subsequent events showed that 'symbolic policy' still prevailed over 'reconciliation policy' in the relations between Hungary and its co-ethnics across the border.

This chapter is organized as follows. First, it puts the Status Law back in the context of Hungarian symbolic policies and the development of European standards for minority protection after the Cold War. Agenda-setting at the COE and the OSCE is then analyzed to show how the originally bilateral controversy quickly became a 'European problem'. The third part of the chapter underlines that the circulation of European standards between these European agencies was intrinsically ambiguous. At the international level, each organization interpreted these norms according to its own history, identity and resources, while at the national level politicians contested the 'European solutions' that they felt were being imposed on them.

[A] 'Nation policy' and minority protection: the Status Law in context

The Status Law exemplifies the discordance between 'symbolic policy' and European political and legal standards for state behavior. Despite the fact that it was presented by its Hungarian advocates as being perfectly in line with the philosophy of European integration, this piece of legislation was primarily perceived in the neighboring countries as an implicit reversal of the Trianon Treaty.

[B] Hungary's relation to ethnic-Hungarians Starting from the interwar period, the acceptance of the 'unjust Trianon Treaty' and the relationship with the diaspora has been an important feature of Hungarian domestic politics and foreign policy. The irredentist policy implemented in the interwar period ultimately failed in 1945. Later on, the postwar Communist governments barely mentioned the situation of the Hungarian minorities in neighboring states in keeping with the façade of socialist brotherhood. However, family and cultural ties to the Hungarian abroad endured and the protests against Ceaucescu's forced assimilation policy in Romania had a galvanizing effect on the opposition to the socialist regime in the late 1980s (Kántor et al, 2004).

As of 1990, the successive Hungarian governments fully revived the issue of the ethnic-Hungarians in public discourses and diplomatic efforts. Hungary introduced a triple-priority foreign policy which consisted in three overlapping objectives: supporting co-ethnics living in neighboring states ('nation policy'); maintaining good neighborly relations; and joining the EU and NATO ('Euro-atlantic integration'). Although these three policies were officially equal in status, finding a balance between them has been a challenge for every Hungarian government v . In order to fulfill their constitutional obligation towards co-ethnics, Hungarian leaders have simultaneously used the bilateral political level (including clauses on national minority protection in all the treaties they signed with neighboring countries) vi and the multilateral forums (putting national minority protection back on the agenda of European organizations). A hierarchy developed which favored the 'nation policy' over the other subpolicies in the late 1990s, due to internal governmental preferences and to pressures from organizations representing the diaspora. It is worth noting that the impeding accession to the EU, and the fear that the Schengen regime would create a 'new Iron Curtain' which would effectively cut off Romania, Croatia and Serbia's Hungarian speakers from Hungary was also a main justification for an intensification of Hungary's approach to its co-ethnics.

The policy instrument designed to strengthen the links with ethnic-Hungarians was a piece of legislation passed in June 2001, in a nearly unanimous vote, by the Hungarian parliament. This framework law was due to enter into force in January 2002. It granted special benefits to the ethnic-Hungarians living in Romania, Slovakia, Serbia, Slovenia, Croatia and Ukraine. The 'Status Law' was to provide access to higher education with the same conditions as Hungarian citizens as well as the possibility of obtaining temporary work permits in Hungary, which amounted to a privileged access to the Hungarian labor market and social welfare system. Families whose two children attended Hungarian speaking schools in these countries were to receive a monthly subsidy. These benefits would be available to persons holding 'Certificates of Hungarian Nationality', essentially ethnic identity cards issued on the recommendation of Hungarian minority organizations located beyond the border. Although the law was meant to encourage ethnic-Hungarians to remain in their homelands, it made the bearers of these certificates legal subjects of Hungarian legislation as well as recognized members of the Hungarian 'nation'. According to the Hungarian authorities, this piece of legislation was perfectly in conformity with the philosophy of European integration because it sought to reduce the significance of territorial borders (Fowler, 2004). More specifically, its proponents argued that it conformed to European standards on national minority protection promoted by the COE and the OSCE.

[B]European standards for minority protection Since its creation in 1949, the COE has adopted a wide range of legal instruments in the field of human rights protection, most notably the 1950 European Charter of Human Rights and Basic Freedoms. After the dissolution of the Soviet bloc, this agency developed specific standards for national minority protection such as the Framework Convention for Protection of National Minorities adopted in 1995. But this text was the result of a difficult compromise between its member states, some of which have not signed, let alone ratified it (Benoit-Rhomer and Klebes, 2005).

The OSCE, created as a forum for East-West dialogue in the early 1970s, was given a mission of stabilization in post-cold war Europe which included addressing ethnic tensions. During the Cold War, the CSCE vii had defended an 'individualist' conception of human rights attached to individuals rather than to groups. After 1989, the participating states repeatedly emphasized the respect of national minority rights as inherent to the promotion of democracy throughout the continent. Yet tensions quickly appeared between the promoters of a traditional conception of sovereignty represented by state rights, and some governments that urged to reformulate this principle in order to guarantee a full protection of national minorities. The Document of the Copenhagen Meeting of the CSCE, for example, stated that protecting 'the ethnic, cultural, linguistic and religious identity of national minorities' was necessary to guarantee 'peace, justice, stability and democracy' (CSCE, 1990, Title In 2001, the HCNM played a role of 'broker' of international norms for the countries involved in the dispute over the Status Law. The Hungarian authorities first informed Max van der Stoel that this piece of legislation was being drafted in April 2001. Choosing a gradual approach based on 'quiet diplomacy' [START_REF] Kemp | Quiet Diplomacy in Action: the OSCE High Commissioner on National Minorities[END_REF] To achieve this goal, the new HCMN engaged in 'shuttle diplomacy'. He studied each article of the Status Law with representatives of the COE, the three countries in conflict and the organizations representing the Hungarian diaspora, on the basis of proposals for revisions put forward by the Hungarian Foreign Office. The OSCE's position was that 'while keeping in mind that there is some legitimacy to keeping contacts with minorities with whom one has certain cultural and linguistic ties, this has to be done according to the rules'. What we do is legal expertise, it is our mission. Of course, it would be wrong to claim that we never take into account political aspects […] since we provide analyses aimed at helping states to adopt Constitutions or laws that respect legal standards. From this perspective, our analysis is never abstract.

We try to understand the reasons for a given disposition and if this disposition is not conform to the standards, we offer to help find a solution that conforms to these standards but is also acceptable in the countries concerned. It is obvious that we keep an eye on the political context. While drafting our report, we took into account sensitivities in Romania and in Hungary. Everyone found in our report, not necessarily what they wanted to hear, but an explanation of each party's positions. xiii The report of the Venice Commission on 'The preferential treatment of national minorities by their kin-state' published in October 2001 thus analyzed several cases of kin-state legislation from a legal point of view (Venice Commission, 2001). It also mentioned the following flaws of the Status Law: its extraterritorial and unilateral dimension; the neglect of the procedures provided by the bilateral treaties; and the discriminatory nature of the socio-economic benefits reserved to ethnic-Hungarians and denied to the other citizens of the neighboring countries. The Venice Commission stressed that differential treatment of citizens of other states could only be truly justified in the areas of education and culture. From September 2001 onward, the Legal and Human Rights Committee of PACE (herein: Legal Committee) had also started to analyze the political and legal aspects of the Status Law. PACE used the report of the Venice Commission not only to evaluate whether the Status Law was conform to international law, but also to urge Hungary to negotiate with its neighbors and to draft a new bilateral treaty, or at least a regulation that would explain the concrete meaning of this piece of legislation. The Venice Commission report was viewed as too partial to Hungary and not detailed enough to serve as guidance for future norms. xiv Characteristically, the analysis of the Status Law carried out by PACE was more openly political, and more critical. This topic evoked fierce debates at the Legal Committee and the initial report drafted by the Dutch rapporteur Erik Jürgens, which called for the complete withdrawal of the law, had to be revised four times until a watered down version was finally adopted. On 31 October 2001, Jürgens asked the Hungarian government to freeze the implementation of the Status Law pending the adoption of his report. The Hungarian administration had initially thought that it would be sufficient to adopt specific regulations over the law's implementation or to sign bilateral agreements with the neighboring [A]The models of reconciliation put forward by European organizations: towards normative convergence?

The solutions to the conflict over the Status Law proposed by European organizations rested jointly on some norms of international law (non-discrimination, cooperation, protection of national minorities as part of the protection of human rights) and on more directly political principles ('spirit of reconciliation', 'friendly relations', the importance of dialogue to ease tensions). They established a normative regime built on legally binding instruments as well as on diplomatic practices that define 'European values'. Yet the ambiguity surrounding certain notions and the multiplicity of forums of arbitration allowed each international organization to defend its own interpretation of the conflict and offer slightly different solutions. Differences were particularly visible on two points: the legitimacy of the protection of national minorities; the behavior expected from Central European states.

[B] The legitimacy of the protection of national minorities by the kin-state

The Venice Commission and PACE agreed on the merits of the protection of national minorities, seen as essential to the stability of Europe and as a part of human rights protection. But PACE stated more firmly that this protection is first of all the responsibility of the home-state (i.e. that state where these individuals live).

The Venice Commission wrote: 'Stability and prosperity, it is well known, cannot be achieved without a satisfactory protection of national minorities. Thus, all the bilateral treaties on friendly relations [signed by Hungary with Slovakia and Romania] contain provisions on the protection of the (respective) minorities' (Venice Commission, 2001, p.21). Yet without denying the primary role of the home-states, it justified minority protection by kin-states by 'the need to defend cultural diversity in Europe'. The highly-publicized analysis of the Venice Commission gave a great legitimacy to the idea that a 'kin-state' may help its 'kin-minority', although these notions don't appear to be firmly rooted in legal doctrine:

The advantage of the [2001 report] was that it was setting some rules. Setting, or rather… identifying, because none of this was invented. It was a field where standards were vague, that is the reason why this was possible. We identified them and we tried to make them clear. It was a new topic…in any case, the international community had neglected [the preferential treatment of kin-minority] although it exists in many Constitutions adopted in the 1980s and it is sometimes expressed in quite strict terms […] It also raised a terminology issue. At the time, we didn't even know which words to use. These words 'kin state', 'kin minorities', some people even said that we invented them. I didn't invent anything. I found that, of course I studied a lot, there were a lot of things on the internet, etc. I read so many articles and books because it was a completely new issue, that's why people said that nothing existed. This is not true, a lot of things existed. I mean, there were things that touched upon the question in an indirect way or through a different angle but a lot of things existed. xvi Similarly, the report of the Legal Committee of PACE adopted on 25 June 2003 stated that 'nobody would wish to gainsay that it is not in the interest of national minorities if an existing kin-state helps citizens belonging to those minorities to be conscious of their identity and to develop it, within the national identity of the state of which they are citizens (PACE, 2003, 45). But the rapporteur highlighted the risk of 'separatism' created by such policies and defined some conditions which have to be met for this protection to be acceptable (first of all, the home-state has to be informed ahead of time and has to agree to the measures proposed by the kin-state).

Similarly, although the High Commissioner on National Minorities of the OSCE used the international norms formalized by the Venice Commission to deliver his own recommendations, his position was more reserved as regards the idea of the 'protection' of citizens of another state. The HCMN's reluctance appeared in his unwillingness to use the terminology of the 'kin-state':

We don't want to legitimize a 'kin-state' perspective for several reasons linked to international law and stability in Europe. It is worth remembering that it is the state's responsibility to protect all the citizens who live on its territory, and even all the non-citizens. We favor multilateral agreements, since organizations like the Council of Europe and the High Commissioner on National Minorities were created after the Second World War to deal with these issues. Moreover, there are bilateral agreements and the International Conciliation and Arbitration Court, so there is really no need for any unilateral decisions. xvii Accordingly, the HCNM's statements clearly underlined the principle of the respect of state sovereignty and the necessity to integrate minorities in their home-state [START_REF] Osce | Sovereignty, Responsibility, and National Minorities: Statement by Rolf Ekeus[END_REF].

[B]The practices expected from European states

The report adopted by the Venice Commission in October 2001 listed the legal norms that European states have to conform to: the respect of territorial sovereignty of states; the principle of pacta sunt servanda (treaties must be respected and performed in good faith); the respect of human rights and fundamental freedoms; the prohibition of discrimination. But the models of reconciliation promoted by the COE and the OSCE also called for states to adopt certain forms of behavior: favoring existing multilateral and bilateral instruments over unilateral measures; engaging in dialogue with neighboring countries to negotiate the implementation of these treaties or to jointly establish new measures; accepting the intervention of European institutions to promote 'friendly relations' and a 'spirit of cooperation'.

For the Venice Commission, the existing instruments for the protection of national minorities have to be implemented according to certain rules, like the principle of 'good neighborly relations', in order to fill the gaps of international law: preferential socio-economic treatment of co-members of the 'nation' (PACE 2003, paragr. 34). The rapporteur concluded his analysis on the idea that a common definition of the 'nation' was missing in Europe and called for the COE to take a further look at the concepts of nation, citizenship and nationality. xx

[A]Conclusion

The model of reconciliation designed by the OSCE and the COE to solve the dispute on the Hungarian Status Law was the temporary outcome of a process that had started in the early 1990s, when the protection of national minorities was again put on the agenda of European organizations. Their involvement in this conflict shows that this emerging 'grammar of reconciliation' was built on some principles of international law, but also on notions that were less established from a legal point of view (such as 'kin-state') and on behaviors implicitly or explicitly required from European states (such as 'good neighborly relations'). This case study showed that European institutions played a dual role in these policies of neutralization of conflicts over the past: a role of framing when they built a pan-European normative regime, in the case of the Venice Commission; a role of broker in the case of the OSCE and PACE, which used these norms to push the conflicting parties to negotiate. These brokers were however not neutral and each European organization introduced its own nuances to these common standards: the more critical approach of the HCNM prevailed over that of the Venice Commission thanks to the willfulness of PACE.

Despite the fact that the dispute over the Status Law found a temporary solution in 2003, several subsequent events have shown that improving the situation of the co-ethnics has remained a high priority for Hungarian foreign policy. In 2005, under strong pressure from the conservative opposition, the socialist government revised its citizenship law, making it easier for ethnic-Hungarians to obtain long-term visas and to get Hungarian citizenship when moving to Hungary. Upon coming back to power in May 2010, a new conservative government took several symbolic measures in the framework of its 'nation policy'. The Hungarian Parliament passed with an overwhelming majority a law that Habsburg Empire. The population of Hungary is currently 10 million. Of the approximately 2.5 million Hungarian speakers who live outside Hungary in the Carpathian Basin, the vast majority live in Romania (1.4 million) and in Slovakia (500,000).

ii The first post-communist president József Antall, for example, famously said upon his election in 1990 that he felt, 'in spirit', the Prime minister of fifteen million Hungarians, thereby including Hungarians across the world in his definition of the Hungarian nation.

iii On 18 July 2003, Romania and Hungary settled their differences over the Status Law by agreeing to extend its benefits to all Romanian citizens, whether ethnic-Hungarians or not. On 19 July 2003, Slovakia and Hungary agreed that Hungary would be entitled to grand benefits for the promotion of the cultural and linguistic identity of the Hungarians in Slovakia based upon their bilateral treaty and not upon the Status Law. In December 2003, they signed a bilateral agreement on the educational and cultural support of the Slovak minority living in Hungary and the Hungarian minority living in Slovakia. In both cases, the Status Law became void (in accordance with EU regulation) when the countries joined the EU: on 1 May 2004 for Slovakia and 1 January 2007 for Romania. iv See (Neumayer, 2007a) for a detailed analysis of the EU's intervention in this dispute.

v The various Hungarian political parties of course hold slightly different views on the best ways to support ethnic-Hungarians but this topic goes beyond the scope of this paper.

vi Such as the 'Basic Treaties' signed with Ukraine (1992), Romania (1995) and Slovakia (1996). [START_REF] Ghebali | L'OSCE dans l'Europe post-communiste, 1990-1996 : vers une identité paneuropéenne de sécurité[END_REF].

viii Ekeus succeeded van der Stoel as HCNM in July 2001.

ix Personal interview with the author, HCNM Office, 30 May 2007.

x All these documents are reprinted in Kántor et al. (2004). xx After studying this issue, PACE concluded that it was impossible to agree on a unique definition of the concept of nation that would be common to all member states [START_REF] Pace | Recommandation 1735[END_REF].

  , he first paid a visit to the Hungarian government in May 2001 and tried to convince them to use the provisions on minority protection in the existing bilateral treaties to improve the situation of their co-ethnics, instead of passing a new law. A few days before the law was examined by the Hungarian Parliament, van der Stoel sent a confidential letter to the Hungarian Prime minister, Viktor Orbán, asking his government to amend the text. Yet 92 percent of members of the Hungarian Parliament voted in favor of the initial version of the text on 12 June 2001. In October 2001, a few days after the COE gave its first public analysis of the Status Law (see below), Max van der Stoel published a declaration of principles entitled 'Sovereignty, responsibility and national minorities' which stated that unilateral measures taken by states to protect their minorities living in foreign countries can create tensions and should be avoided. He also underlined the necessity to respect state sovereignty. Hungary was not explicitly mentioned in this short analysis (OSCE, 2001). Despite the signing in December 2001 of a Hungarian-Romanian memorandum on the implementation of the Status Law which partially reduced the tensions between these two countries, the new HCNM Rolf Ekeus viii still called for major amendments to the Status Law in January 2002.

  ix In June 2003, the day after the Hungarian Parliament adopted a final, and largely modified, version of the Status Law, the High Commissioner made a final public declaration in which he insisted on the risks of destabilization in the region. This time, he clearly mentioned Hungary and warned of 'Status Law precedent', for fear that this law might become a model for states which had shown a strong interest in their co-ethnics, like Russia and Serbia. x [B]The COE: legal standards and 'parliamentary democracy' The long intervention of the COE in the rewriting of the Status Law between 2001 and 2003 shows how Romanian and Slovak delegates tried to give the maximum publicity to this controversy, whereas the Hungarian members of the Assembly were keen to put the Status Law in a regional context and to discuss it behind closed doors. Just a week after the Hungarian parliament adopted its first version on 19 June 2001, the Romanian delegation at the COE prepared a draft resolution (signed by every Slovak member of the Parliamentary Assembly, except for one ethnic-Hungarian) that prompted the Parliamentary Assembly of the Council of Europe (PACE) to call upon Hungary not to implement the Status Law. Two days later, the Hungarian members of PACE launched a counterattack and submitted several proposals promoting cross-border collaboration to protect the identity of national minorities. The same day, the Romanian Prime minister requested the the COE's Commission for Democracy through Law, also called 'Venice Commission' xi , to examine the law. On 29 June, the Standing Committee of PACE xii decided to refer the Hungarian and Romanian initiatives to the Venice Commission, to report on. On 6July, the Venice Commission accepted the proposal of the Hungarian Foreign minister, requesting a comprehensive study of the protection of minorities in Europe and rejected the one submitted by the Romanian head of government, asking for an opinion only on the Hungarian law. By agreeing to develop a comparative approach that would not single out Hungary, the Venice Commission toned down its political role and allowed Budapest to save face:

  vii The Conference for Security and Cooperation in Europe ended with the signature of the Helsinki Act in 1975. It was institutionalized and renamed Organization for Security and Cooperation in Europe in 1994

xi

  The Venice Commission is a consultative body established by the COE in 1990. Its members are legal experts nominated by their governments. Its official mission is to 'contribute to the dissemination of the European constitutional heritage, based on the continent's fundamental legal values. [It also plays a role] in crisis management and conflict prevention through constitution building and advice' (Venice Commission, 2007). xii The Standing Committee of PACE consists of the Chairpersons of national delegations and the Bureau (the President, twenty Vice-Presidents, the Chairpersons of the political groups as well as the Chairpersons of the general PACE Committees). xiii Personal interview with the author, Venice Commission, 22 November 2005. xiv Personal interview with the author, COE, 23 November 2005. xv These decrees regarded the procedures of issuing the Hungarian certificate as well as student benefits, cultural benefits and education. xvi Personal interview with the author, Venice Commission, 22 November 2005. xvii Personal interview with the author, HCNM Office, 31 May 2007. xviii Personal interview with the author, Venice Commission, 22 November 2005.xix The Preamble to the first draft of the Status Law read: 'In order to ensure that Hungarians living in neighboring countries form part of the Hungarian nation as a whole, and to promote their well-being and awareness of national identity within their home country…'. It was replaced in the amended law passed in June 2003 by the following: 'In order for the Republic of Hungary to meet its obligations to Hungarians living outside Hungary and to promote the preservation and development of their manifold relations with Hungary…'(Kántor et al, 2004, 508).

IV, paragr. 30) but failed to give a precise definition of the notion of 'national minority'. This fundamental ambiguity weakened the international legal standards subsequently adopted by the OSCE.In 1992, the Dutch diplomat Max van der Stoel was appointed the first High Commissioner on National Minorities (HCNM) of the OSCE, with the task of providing 'early warning' and 'early action' in regard to tensions involving national minority issues. Because Western democracies were reluctant to grant this institution a say in their own minority policies, and for fear of encouraging separatist movements in Eastern Europe, its scope of action was restricted to minorities 'which present a threat for security'. The construction of international standards by the HCNM was thus based on a restrictive interpretation of what constitutes a 'minority issue' in Western Europe (excluding terrorism, so as to leave Northern Ireland and the Basque Country aside) alongside a pragmatic acceptation of this international legal framework by Eastern Europe states, in the hope of a future integration into European institutions. Van der Stoel developed two parallel approaches to minority protection: the normative path based on the norms of the OSCE and the COE; 'preventive diplomacy' based on confidentiality and, when necessary, on a policy of 'name and shame' whereby the countries which do not respect international norms are publicly singled out(Chandler, 1999).[A] Agenda setting in European organizationsThe timing and methods of the involvement of the European organizations in the conflict over the Status Law between 2001 and 2003 showed a division of labor between these agencies, according to their raison d'être and to their tools. The COE occupied the front stage of the diplomatic and the media forums and turned certain notions and principles into legal norms, while the OSCE relied on this legal expertise to act as an intermediary between the Hungarian, Romanian and Slovak governments.[B]The 'quiet diplomacy' of the OSCE

governments to respond to international criticism. Although the Hungarian government announced on 7 June 2002 that it has drafted amendments to the Status Law, the report which was examined by the Legal Committee of PACE on 24 June still called for the withdrawal of the law. Realizing that the problem was the content of the law itself, the Hungarian government informed PACE that it planned to further amend this legislation according to the recommendations made by the Venice Commission. On 3 March 2003, the Legal committee of PACE finally adopted the Jürgens report with 22 members voting for the report, 13 abstaining and none voting against it. On 23 June 2003, the amendment of the Status Law on work, health and travel benefits was passed by the Hungarian Parliament by a 53% majority. The law's entire focus was changed to supporting Hungarian language and culture.

Nevertheless, the Romanian and Slovak Permanent delegations at PACE insisted that the report be presented at the Assembly's plenary session on 25 June 2003, whereas the Hungarian delegation claimed that submitting to public opinion a dispute involving several states would be contrary to the spirit of the Assembly. PACE finally adopted the Jürgens report on that day with 95 votes pro, 11 votes against and 10 abstentions. A resolution from the Legal Committee asked for further changes to the law and negotiations with the neighboring countries over its implementation.

Certain parts of the Hungarian law were very well received by some members of the Commission and absolutely not accepted by others. For example, the 'Certificate of Hungarian Nationality'... It was a document with anagraphic data, a photo, which could have been used in Hungary as an identity card.

The question was: is it acceptable for a state to deliver to foreign citizens an identity document that looks like an identity card? Half of the Commission replied: 'Absolutely not!'. And the other half: 'Why not?' It was difficult to say… leaving the issue of the political link aside, from the point of view of international law, it is quite difficult to answer this question. That's why we fell back on the principle of good neighborly relations: 'do not create tension. I mean, if you know that a given act will provoke tensions, you must at least use a bilateral procedure that exists anyway in minority issues'… so we had to look at all this from quite a broad context. xviii By contrast, the Legal Committee of PACE underlined the sensitivity of national minority issues in Central Europe and openly questioned the motivations of the Hungarian government for drafting this law -thus recalling some of the reproaches formulated by Romania and Slovakia, such as the meddling in their internal affairs and an implicit will to recreate the borders of Greater Hungary. The Jürgens report adopted on 25 June 2003 highlighted the ambiguity of the definition of the term 'nation' in the preamble of the Status Law: 'There is a feeling in these neighboring countries that the definition of the concept of 'nation' in the preamble to the law could under certain circumstances be interpreted -though this interpretation is not correct -as non-acceptance of the state borders which divide the members of the 'nation', notwithstanding the fact that Hungary has ratified several multiand bilateral instruments containing the principle of respect for the territorial integrity of states, in particular the basic treaties which have entered into force between Hungary and Romania and Slovakia' xix (PACE 2003, paragr. 10).

The report also established that the Hungarian authorities violated the principle of non-discrimination.

According to Jürgens, giving socio-economic benefits through working permits and inclusion in the healthcare system could not be considered as 'a form of assistance to a kin minority to preserve its identity. It was a form of selection of workers from a foreign country which clearly served the allows individual ethnic-Hungarians to apply for Hungarian citizenship if they can prove that they are of Hungarian origin and speak the language. A month later, it declared 4 June a 'Day of National