4 resultados para Placed-based Community Engagement
em Digital Commons - Michigan Tech
Resumo:
The Cliff Mine, an archaeological site situated on the Keweenaw Peninsula of Michigan, is the location of the first successful attempt to mine native copper in North America. Under the management of the Pittsburgh & Boston Mining Company from 1845-1879, two-third of the Cliff’s mineral output was in the form of mass copper, some pieces of which weighed over 5 tons when removed from the ground. The unique nature of mass copper and the Cliff Mine’s handling of it make it one of the best examples of early mining processes in the Keweenaw District. Mass copper only constituted 2% of the entire product of the Lake Superior copper districts, and the story of early mining on the Peninsula is generally overshadowed by later, longer running mines such as the Calumet & Helca and Quincy Mining Companies. Operating into the mid-twentieth century, the size and duration of these later mines would come to define the region, though they would not have been possible without the Cliff’s early success. Research on the Cliff Mine has previously focused on social and popular history, neglecting the structural remains. However, these remains are physical clues to the technical processes that defined early mining on the Keweenaw. Through archaeological investigations, these processes and their associated networks were documented as part of the 2010 Michigan Technological Archaeology Field School’s curriculum. The project will create a visual representation of these processes utilizing Geographic Information Systems software. This map will be a useful aid in future research, community engagement and possible future interpretive planning.
Resumo:
This thesis considers the impact that discursive and community practices have on women’s access to the public sphere by examining female cyclists and a cycling community in Miami, Florida via interviews and observation. In the interviews, female cyclists frequently reported fears for their safety, including concern over harassment, when riding in public space. I interviewed participants of the cycling community and observed Emerge Miami’s meetings and events, where publicly organized cycling excursions were a major component. Using the theoretical and methodological lenses of Feminist Critical Discourse Analysis and Communities of Practice, I examined the interviews to understand how participants discursively framed and contextualized gender-based harassment. I found two meta-discourse frames in operation: a normative frame (that essentially accepted the status quo) and a feminist frame (that challenged the “naturalness” of women’s harassment as just what one had to live with). The feminist frame offered a pathway for women to exert control over their experiences and alter the cultural understanding of harassment’s meaning and effect. The local community practices of Emerge Miami also challenged the normative frames that often silence women, employing explicitly invitational practices, which demonstrates how local discursive and social activity can impact and increase women’s involvement by creating a more accessible space for women to engage with their local cycling community.
Resumo:
Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.
Resumo:
This project consists of a proposed curriculum for a semester-long, community-based workshop for LGBTQIA+ (lesbian, gay, bisexual, trans*, queer or questioning, intersex, asexual or ally, "+" indicating other identifications that deviate from heterosexual) youth ages 16-18. The workshop focuses on an exploration of LGBTQIA+ identity and community through discussion and collaborative rhetorical analysis of visual and social media. Informed by queer theory and history, studies on youth work, and visual media studies and incorporating rhetorical criticism as well as liberatory pedagogy and community literacy practices, the participation-based design of the workshop seeks to involve participants in selection of media texts, active analytical viewership, and multimodal response. The workshop is designed to engage participants in reflection on questions of individual and collective responsibility and agency as members and allies of various communities. The goal of the workshop is to strengthen participants' abilities to analyze the complex ways in which television, film, and social media influence their own and others’ perceptions of issues surrounding queer identities. As part of the reflective process, participants are challenged to consider how they can in turn actively and collaboratively respond to and potentially help to shape these perceptions. My project report details the theoretical framework, pedagogical rationale, methods of text selection and critical analysis, and guidelines for conduct that inform and structure the workshop.