aspects of the matters at hand. As in any other closed decision-making system, a wealth of rumors dominate the current perception of the actions taken by the government and telecommunications companies. Where these rumors are mentioned, they are discussed in order to test validity, and not cited as evidence.

This paper is not intended to be comprehensive, and we err on the side of brevity where possible. Toward these ends, our contributions are threefold:

1.  outline a methodology for the detection of the disruption of network performance and infer purposeful intent based on indicators, differentiated from normal network failures;

2.  begin to identify potential periods of throttling, based on available historical data;

3.  attempt to enumerate those institutions that are not subject to interference.

The experiments described herein are motivated toward collecting initial, open-ended data on an opaque phenomenon; where possible our results and code are publicly available for outside investigation at:

> <http://github.com/collina/Throttling>

The remainder of this paper is structured as follows. In the following section, we identify the infrastructural properties of networks relevant to our line of inquiry that enable states and intermediaries to control access to content and service performance. We describe the dataset core to our 