Weaving frames of knowledge

Abstract

Colonial representatives can be unreliable narrators, as their descriptions were often value judgements of how closely people adhered to similar material and non-material cultures of the coloniser’s place of origin. Yet often they are some of the only narrations we have, and so we must filter through biases to examine Indigenous lifeways at contact. This is true for Jesuit contact with Aztecs, for Caesar’s contact with the Gauls, and of course for colonial contact with Aboriginal Australians. With appropriate caution, we can use these narratives to better understand the past, leveraging the past as a calibration dataset for understanding our present and future. Dark Emu challenges the assumptions of what the term ‘hunter-gatherer’ meant in early colonist narratives. Recent research suggests that humans were critical as seed dispersal agents and were engaged in practices that helped promote animal reproduction (Baynes-Rock 2020; Crabtree et al. 2019). According to Pascoe, this places these cultures within the purview of farming. Yet Porr and Vivian-Williams suggest that Pascoe engages with the antiquated progression of a cultural-historical trajectory from hunting-gathering to farming that he refuted for most of his career. A large challenge for Pascoe, other scientists and science communicators, is recognising the complexities and, at times contradictions, inherent in interweaving different knowledge systems. Weaving Western scientific knowledge, knowledge gleaned from unreliable colonial representatives, and knowledge from contemporary Aboriginal people to triangulate the past is an inherently political endeavour. The debates on dominant past Aboriginal lifeways and what this means for society today is particularly fraught due to the persistent social inequities faced by Indigenous peoples worldwide. Successful collaboration in interweaving knowledge systems generally involves iterating through cycles of knowledge mobilisation, translation, negotiation, synthesis and application (Teng€ o et al. 2017). All knowledge systems are imperfect and any effort to iterate through cycles of knowledge weaving are imperfect, but these efforts can help diverse groups reach applications of this knowledge that are more acceptable than neglecting the steps of this process. Scientific research often infers patterns in the absence of hard data, building models based on our understanding of current and past trends. To build the most parsimonious model, we base them off observable truths. These observations, by necessity, have to be simple and somewhat irrefutable, and we build up complexity from the simplest beginnings. In a recent paper that Porr and Vivian-Williams cite, for example, Crabtree et al. (2021a) build models based on underlying geographic features of the Last Glacial Maximum supercontinent of Sahul. They include data from Binford’s ‘Constructing Frames of Reference’ on human travellers coupled with ethnographic observation, as well as models of visibility across the whole continent, and data on the relative difficulty or ease of travel across the continent. After conducting 125 billion simulations, the authors identify the most frequently travelled routes, calling them ‘superhighways’. As with models in astrophysics, epidemiology, or economics, the authors follow the principles of parsimony: building a model from testable, observable facts, and only when examining those, building to new complexity (Romanowska et al. 2021). In a follow-up piece, Crabtree et al. (2021b) note their plans to build on the simple model to explore more social questions. Yet, Porr and Vivian-Williams suggest that Crabtree et al.’s reliance on testable, observable quantities, ‘erases options to learn from the past and challenge the present’ by ‘mak[ing] the deep past accessible to a modern audience because it is the language of Western modernity’. Computational models, we would argue, when woven with data from traditional and local ecological knowledge, can