CommunityPulse: Facilitating Community Input Analysis by Surfacing Hidden Insights, Reflections, and Priorities

Virtually all public works projects require a substantial planning effort to identify impacts, costs, and alternatives. Federal and state laws and regulations call for certain levels of public involvement during planning, but meaningful, collaborative public involvement entails doing more than the minimum requirements. This is particularly true when there appears to be an imbalance in public input, where one viewpoint is heard above others. The San Diego Metropolitan Transit Development Board (MTDB) has undertaken efforts on two corridor projects to expand its public involvement in ways that maximize the range of community views, enhance project design, and build support for the project. In addition to the traditional public meetings, newsletters, and open houses, MTDB has used public relations firms, neutral facilitators, and staff outreach to achieve expanded public involvement goals. MTDB has found that, while there are risks and costs associated with these approaches, they ultimately result in better projects that receive more widespread public and political acceptance.

Download Full-text

Organized Trash Collection in Saint Paul: Report on Community Input and Draft Goals and Objectives

SSRN Electronic Journal ◽

10.2139/ssrn.2816159 ◽

2016 ◽

Author(s):

Jasper L. Tran

Keyword(s):

Saint Paul ◽

Community Input ◽

Goals And Objectives

Download Full-text

Comprehensive strategy for capturing and integrating community input into community research training curricula

Journal of Clinical and Translational Science ◽

10.1017/cts.2018.11 ◽

2018 ◽

Vol 2 (1) ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Jennifer Cunningham-Erves ◽

Yvonne Joosten ◽

Marino A. Bruce ◽

Jared Elzey ◽

Patrick Luther ◽

...

Keyword(s):

Research Training ◽

Community Research ◽

Limited Information ◽

Community Members ◽

Additional Time ◽

Face To Face ◽

Community Stakeholders ◽

Training Frequency ◽

Training Topic ◽

Community Input

IntroductionCommunity stakeholders often participate in community research training curricula development. There is limited information describing how their input informs curricula. This paper describes input solicitation methods, input received, and examples of its integration.MethodsFrom June 2014 to June 2016, community members (CMs) and community-based organizations (CBOs) guided curricula development tailored for CMs and CBOs, respectively. Engagement methods included a strategic planning retreat, surveys, a listening session, workgroup meetings, and community engagement studios. Descriptive statistics were used to summarize survey input. For other methods, input was extracted and compiled from facilitator notes.ResultsCMs (n=37) and CBOs (n=83) providing input included patients and caregivers and advocacy, community service, and faith-based organizations, respectively. The major feedback categories were training topic priorities, format (e.g., face-to-face vs. online), logistics (e.g., training frequency), and compensation (e.g., appropriateness). Input directly guided design of CBO and CM curricula (e.g., additional time devoted to specific topics based on feedback) or helped to finalize logistics.ConclusionsMultiple quantitative and qualitative methods can be used to elicit input from community stakeholders to inform the development of community research training curricula. This input is essential for the development of training curricula that are culturally relevant and acceptable.

Download Full-text

A case of stunted development? Existential reasoning is contingent on a developing theory of mind

Behavioral and Brain Sciences ◽

10.1017/s0140525x06319103 ◽

2006 ◽

Vol 29 (5) ◽

pp. 471-472 ◽

Cited By ~ 10

Author(s):

E. Margaret Evans ◽

Henry M. Wellman

Keyword(s):

Theory Of Mind ◽

Developmental Trajectory ◽

Developmental Framework ◽

Evolutionary Origins ◽

Community Input

Missing from Bering's account of the evolutionary origins of existential reasoning is an explicit developmental framework, one that takes into account community input. If Bering's selectionist explanation was on target then one might predict a unique and relatively robust developmental trajectory, regardless of input. Evidence suggests instead that children's existential reasoning is contingent on their developing theory of mind.

Download Full-text

Remaking Chicago’s Industrial Spaces

10.5406/illinois/9780252040597.003.0007 ◽

2017 ◽

Author(s):

Carrie Breitbach

Keyword(s):

Real Estate ◽

Working Class ◽

Economic Base ◽

Steel Mill ◽

City Policy ◽

Community Input

This chapter recounts deindustrialization and redevelopment plans at the site of a former steel mill in Southeast Chicago over a period of approximately two decades. Beginning with an overview of the foundation of the working-class landscapes that were built up around the steel mill, the chapter charts the plant’s closure, then follows shifts in city policy and rhetoric accompanying various iterations of redevelopment plans. This narrative chronicles the rise of a neoliberal economic base dependent on real estate and other tertiary sectors, instead of industry, and it makes an argument for the necessity of community input into redevelopment schemes.

Download Full-text

Extending Ocean Drilling Pursuits [eODP]: Making Scientific Ocean Drilling Data Accessible Through Searchable Databases

10.5194/egusphere-egu2020-8069 ◽

2020 ◽

Author(s):

Andrew Fraass ◽

Leah LeVay ◽

Jocelyn Sessa ◽

Shanan Peters

Keyword(s):

User Interfaces ◽

Large Scale ◽

Ocean Drilling ◽

Marine Sedimentation ◽

Drilling Data ◽

Working Groups ◽

Age Model ◽

International Ocean Discovery Program ◽

Community Input ◽

Derived Data

<p>Scientific ocean drilling through the International Ocean Discovery Program (IODP) and its predecessors, has a far-reaching legacy. They have produced vast quantities of marine data, the results of which have revolutionized many geoscience subdisciplines. Meta-analytical studies from these efforts exist for micropaleontology, paleoclimate, and marine sedimentation, and several outstanding resources have curated and made available elements of offshore drilling data (e.g., Neptune), but much of the data remain heterogeneous and dispersed. Each study, therefore, requires reassembling a synthesis of data from numerous sources; a slow, difficult process that limits reproducibility and slows the progress of hypothesis testing and generation. A computer programmatically-accessible repository of scientific ocean drilling data that spans the globe will allow for large-scale marine sedimentary geology and micropaleontologic studies and may help stimulate major advances in these fields.</p><p>The eODP project, funded through the NSF&#8217;s EarthCube program, seeks to facilitate access to, and visualization of, these large microfossil and stratigraphic datasets. To achieve these goals, eODP will be linking and enhancing the existing database structures of the Paleobiology Database (PBDB) and Macrostrat. This project is targeting shipboard drilling-derived data, but the infrastructure will be put in place to allow the addition of data generated post-cruise. eODP will accomplish the following goals: (1) enable construction of sediment-grounded and flexible age models in an environment that encompasses the deep-sea and outcrops; (2) expand existing lithology and age model construction approaches in this integrated offshore-onshore stratigraphically-focused environment; (3) adapt key microfossil data into the PBDB data model; (4) develop new API-driven web user interfaces for easily discovering and acquiring data; and (5) establish user working groups for community input and feedback. The success of eODP hinges upon interaction, feedback, and contribution of the scientific ocean drilling community, and we invite anyone interested in participating in this project to join the eODP team.</p>

Download Full-text

Refining the clinical trials assessment of infrastructure matrix tool.

Journal of Clinical Oncology ◽

10.1200/jco.2014.32.30_suppl.230 ◽

2014 ◽

Vol 32 (30_suppl) ◽

pp. 230-230

Author(s):

Bryan Weiner ◽

Randall Teal ◽

Eileen P. Dimond ◽

Marjorie J. Good ◽

Angela Carrigan ◽

...

Keyword(s):

Clinical Trials ◽

Best Practice ◽

Research Performance ◽

Cognitive Interviews ◽

Clinical Practices ◽

Scoring Method ◽

Team Members ◽

Program Leaders ◽

Don't Know Responses ◽

Community Input

230 Background: Many community cancer research programs aim to exceed Good Clinical Practices. To support such efforts, the National Cancer Institute and collaborators began developing the Clinical Trials Assessment of Infrastructure Matrix (CT AIM) Tool in 2008. CT AIM’s 3 levels of exemplary performance span 11 infrastructure attributes. 2013’s revisions focused on interpretability, usability, and measurability. Methods: Tool input was obtained at national research meetings. Also, 4 Principal Investigator-Program Administrator (PI/PA) pairs from NCI-funded community cancer programs with varied demographics (eg, size, population) underwent cognitive interviews. Aggregated responses and a major-themes summary led to tool revisions. Next a web-based version was piloted with 4 more PI/PA pairs. The frequency/distribution of responses within pairs was assessed. The revised tool was then field-tested with 9 more PIs and scoring method feedback was collected; the tool was further revised. Results: Per community input and cognitive interviews: (1) “best practice” designation was replaced with “assessment of infrastructure”, (2) attributes were reordered based on perceived importance, (3) terms and cumulativeness of levels were clarified. Receiving 0 “don’t understand”s indicated improvement in clarity. 64% of “don’t know” responses were from respondents at the same program and 5 were from the biospecimen research attribute, indicating the information is difficult for programs to obtain. PI/PA responses varied 36% of the time, of which 70% involved a 1-level difference in response, indicating variation in responses by program role. 2 questions generated inconsistent responses from all 4 pairs, indicating possible further revisions. Average scoring was more accurate and sensitive to incremental program improvements. Conclusions: Broad community input, cognitive interviews, and piloting improved the tool’s clarity. Program leaders are encouraged to use CT AIM with research team members to enhance site infrastructure. CT AIM is useful for quality improvement, benchmarking research performance, progress reporting, and communicating program needs with institutional leaders. NCI Contract No. HHSN261200800001E

Download Full-text