Anambra poll: INEC trains staff on violence mitigation

The Independent National Electoral Commission (INEC) has commenced the training of its officers on the application of Election Mitigation and Advocacy Tool (EVMAT).

The training, being conducted in Awka, capital of Anambra, is in preparation for the Nov. 18 governorship election in the state.

INEC Director of Voter Education and Publicity, Oluwole Osaze-Uzzi, made the disclosure in a statement issued to newsmen on Wednesday in Abuja.

Osaze-Uzzi said the training was organised by The Electoral Institute (TEI), training and research arm of INEC.

He said the training was aimed at developing the capacity of the participants to deploy violence reduction mechanisms to minimise electoral risks during the governorship poll.

The statement quoted the Acting Director-General of TEI, Dr Sa’ad Idris, as saying that proper application of EVMAT was key in reducing risk of violence during election.

Idris said the training was geared toward equipping the participants with the necessary skills to effectively administer EVMAT in their respective local government areas.

“The standardised EVMAT offers unique opportunities for all stakeholders in the electoral process to effectively prevent and mitigate election violence.

“The instrument possesses higher predictive power that can help appreciate main risk factors through early warning that may inform proactive response.

“INEC in recent past has deployed the EVMAT instrument in a bid to test the pulse of various players in order to accurately predict and advise on actions to be taken by those responsible for securing elections.

“The effective application of this instrument will determine the level of accuracy of report and risk factor mapping emanating therefrom,” he said.

According to Idris, the participants were carefully selected to receive the training before being deployed to the various local government areas to administer the instruments which would be analysed and coded by a data analyst.

He added that successful risk mapping could only be achieved using accurate data.