Accepted paper:

"We owe a historical debt to no-one": the rehabilitation and mobilisation of photographic images from a museum collection by Kachin youth

Authors:

Helen Mears (University of Brighton)

Paper short abstract:

This paper explores the use of historical photographic images taken by a British colonial officer and amateur anthropologist, in a 2014 music video created by the Kachin artist Bawmwang Ja Raw ('Kaw Kaw'): Labau hte nga ai amyu ('a race with history').

Paper long abstract:

In a 2014 music video by Kachin artist Bawmwang Ja Raw ('Kaw Kaw') the singer appeals to the nationalist sentiment of her listeners, presumed to be Kachin youth. The video to the track 'Labau hte nga ai amyu' ('a race with history') includes footage of dancers in clothing inspired by traditional Kachin dress at a showground built for the largescale Kachin manau festival located in Mangshi, southern China, not far from Laiza on the Burma/China border, headquarters of the Kachin Independence Organization. In making her claim for being a 'race' with 'history' the artist makes use of photographic images of Kachin people created in 1920s by a British colonial officer. These images, which appear in the video as a backdrop to the singer who performs in rap/hip-hop mode, were taken by James Henry Green, a recruiting officer for the Burma Rifles and an amateur anthropologist. His collection of 1400 images and 230 textile items are now in the care of Brighton Museum & Art Gallery (UK). Despite the layering of historical references in the video and the track itself, Bawmwang Ja Raw insists in the song's lyrics that 'labau hka kadai hpe mung nkap' ('we owe a historical debt to no-one'). This paper will explore how politically-engaged and educated Kachin youth living in diaspora are mobilising and rehabilitating cultural resources such as those held at Brighton Museum to visualise cosmo-optimal pasts and futures; futures based on political possibilities as yet unrealised.

panel P089
Re-visioning material anthropological legacies for cosmo-optimal futures