Itaataatawi: Hopi Song, Intellectual Property, and Sonic Sovereignty in an Era of Settler-Colonialism

Hopi traditional songs or taatawi are more than aesthetic objects; they are sound-based expressions of Hopi authority. As I argue in this dissertation, creating, performing, circulating, and remembering taatawi are what we might call acts of sonic sovereignty: a mode of authority articulated within ongoing, sound-based networks that include Hopi people, plants, weather systems, land, and other living things within Hopi territories. I begin by exploring the generative process through which taatawi do their connective work, which includes long-term collaborations between yeeyewat (composers) and environmental actors that establish a collective vision of prosperity that is realized when these songs are performed. Hopi composer Clark Tenakhongva’s taatawi performances during Grand Canyon National Park’s Centennial (a Hopi sacred space currently controlled by settler governments) exemplify the ways Hopi people are actively using taatawi to (re)assert Hopi relations to colonized territories. Because taatawi are closely tied to Hopi relations to one another and the land, and sometimes contain specialized forms of knowledge held closely by Hopi clans and ceremonial societies, their ownership and circulation remains of vital concern to Hopi people. Laura Boulton’s recording of Hopi singers Dan Qötshongva, Thomas Bahnaqya and David Monongye in the Summer of 1940, and the travels of those recordings afterwards, show us the complex politics of Hopi song circulation in the early Twentieth Century up through the present, and how settler cultural and intellectual property laws provide only limited possibilities for indigenous groups seeking to bring their ancestors’ voices back under their control. And even if tribes could reclaim taatawi under settler property laws, these laws require physical and conceptual transformations that effectively sever them from the networks of relations from which they were created. To better support Hopi sonic sovereignty going forward, I offer brief sketches for three potential interventions: (1) an indigenous works amendment to the United States Copyright Act; (2) the use of indigenized licensing frameworks to embed indigenous protocols into the governance and circulation of indigenous creative works both on and off indigenous lands; and (3) establishing a right to indigenous care, similar to Europe’s right to forget, whereby our ancestors’ voices can be subject to indigenous care rather than preserved anonymously and perpetually as archival objects. My hope is that these will allow indigenous communities to better assert and maintain control over their modes of sonic sovereignty despite the increasing colonization of the sonic world by global intellectual property regimes

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

Recent self-supervised pretraining methods for object detection largely focus on pretraining the backbone of the object detector, neglecting key parts of detection architecture. Instead, we introduce DETReg, a new self-supervised method that pretrains the entire object detection network, including the object localization and embedding components. During pretraining, DETReg predicts object localizations to match the localizations from an unsupervised region proposal generator and simultaneously aligns the corresponding feature embeddings with embeddings from a self-supervised image encoder. We implement DETReg using the DETR family of detectors and show that it improves over competitive baselines when finetuned on COCO, PASCAL VOC, and Airbus Ship benchmarks. In low-data regimes, including semi-supervised and few-shot learning settings, DETReg establishes many state-of-the-art results, e.g., on COCO we see a +6.0 AP improvement for 10-shot detection and over 2 AP improvements when training with only 1\% of the labels. For code and pretrained models, visit the project page at https://amirbar.net/detregComment: CVPR 2022 Camera Read

Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

Large, pretrained models are commonly finetuned with imagery that is heavily augmented to mimic different conditions and scales, with the resulting models used for various tasks with imagery from a range of spatial scales. Such models overlook scale-specific information in the data for scale-dependent domains, such as remote sensing. In this paper, we present Scale-MAE, a pretraining method that explicitly learns relationships between data at different, known scales throughout the pretraining process. Scale-MAE pretrains a network by masking an input image at a known input scale, where the area of the Earth covered by the image determines the scale of the ViT positional encoding, not the image resolution. Scale-MAE encodes the masked image with a standard ViT backbone, and then decodes the masked image through a bandpass filter to reconstruct low/high frequency images at lower/higher scales. We find that tasking the network with reconstructing both low/high frequency images leads to robust multiscale representations for remote sensing imagery. Scale-MAE achieves an average of a $2.4 - 5.6\%$ non-parametric kNN classification improvement across eight remote sensing datasets compared to current state-of-the-art and obtains a $0.9$ mIoU to $1.7$ mIoU improvement on the SpaceNet building segmentation transfer task for a range of evaluation scales

APC2 is critical for ovarian WNT signalling control, fertility and tumour suppression

Background Canonical WNT signalling plays a critical role in the regulation of ovarian development; mis-regulation of this key pathway in the adult ovary is associated with subfertility and tumourigenesis. The roles of Adenomatous polyposis coli 2 (APC2), a little-studied WNT signalling pathway regulator, in ovarian homeostasis, fertility and tumourigenesis have not previously been explored. Here, we demonstrate essential roles of APC2 in regulating ovarian WNT signalling and ovarian homeostasis. Methods A detailed analysis of ovarian histology, gene expression, ovulation and hormone levels was carried out in 10 week old and in aged constitutive APC2-knockout (Apc2−/−) mice (mixed background). Statistical significance for qRT-PCR data was determined from 95% confidence intervals. Significance testing was performed using 2-tailed Student’s t-test, when 2 experimental cohorts were compared. When more were compared, ANOVA test was used, followed by a post-hoc test (LSD or Games-Howell). P-values of < 0.05 were considered statistically significant. Results APC2-deficiency resulted in activation of ovarian WNT signalling and sub-fertility driven by intra-ovarian defects. Follicular growth was perturbed, resulting in a reduced rate of ovulation and corpora lutea formation, which could not be rescued by administration of gonadotrophins. Defects in steroidogenesis and follicular vascularity contributed to the subfertility phenotype. Tumour incidence was assessed in aged APC2-deficient mice, which also carried a hypomorphic Apc allele. APC2-deficiency in these mice resulted in predisposition to granulosa cell tumour (GCT) formation, accompanied by acute tumour-associated WNT-signalling activation and a histologic pattern and molecular signature seen in human adult GCTs. Conclusions Our work adds APC2 to the growing list of WNT-signalling members that regulate ovarian homeostasis, fertility and suppress GCT formation. Importantly, given that the APC2-deficient mouse develops tumours that recapitulate the molecular signature and histological features of human adult GCTs, this mouse has excellent potential as a pre-clinical model to study ovarian subfertility and transitioning to GCT, tumour biology and for therapeutic testing