Challenging Folk Icons - Rewriting Woody and Santeri

Woody Guthrie’s song, “The 1913 Massacre,” written around 1940-41, has become something of a folk anthem for progressives, leftists, and labor supporters. It depicts the Italian Hall Disaster of December 24, 1913, in a plainspoken and colorful way, but has been (rightfully) described as “deeply flawed historically.” Much like Guthrie’s English-language folk songs, Finnish immigrant Santeri Mäkelä had a major impact on capturing the working-world around him. Mäkelä’s lyrics for the “Kaivantomiehen Laulu (The Miners’ Song)” were first published in Hancock, 1909, in “Uusi Työväen Laulukirja (The New Workers’ Songbook),” and was probably sung widely by Finnish strikers during the 1913-14 Michigan Copper Strike. Leading up to, and during this Strike Centennial year, there have been renewed performances of the song, both in Finland and the United States—but only in the original Finnish language. This presentation will delve into the accuracy, history, and lyrics of these two important, but historically problematic labor songs.

INVESTIGATION OF AIR JIGGING AND AIR CLASSIFICATION TO RECOVER METALLIC PARTICLES FROM ANALYTICAL SAMPLES

Analyzing “nuggety” gold samples commonly produces erratic fire assay results, due to random inclusion or exclusion of coarse gold in analytical samples. Preconcentrating gold samples might allow the nuggets to be concentrated and fire assayed separately. In this investigation synthetic gold samples were made using similar density tungsten powder and silica, and were preconcentrated using two approaches: an air jig and an air classifier. Current analytical gold sampling method is time and labor intensive and our aim is to design a set-up for rapid testing. It was observed that the preliminary air classifier design showed more promise than the air jig in terms of control over mineral recovery and preconcentrating bulk ore sub-samples. Hence the air classifier was modified with the goal of producing 10-30 grams samples aiming to capture all of the high density metallic particles, tungsten in this case. Effects of air velocity and feed rate on the recovery of tungsten from synthetic tungsten-silica mixtures were studied. The air classifier achieved optimal high density metal recovery of 97.7% at an air velocity of 0.72 m/s and feed rate of 160 g/min. Effects of density on classification were investigated by using iron as the dense metal instead of tungsten and the recovery was seen to drop from 96.13% to 20.82%. Preliminary investigations suggest that preconcentration of gold samples is feasible using the laboratory designed air classifier.