Civil Infrastructure Decision Making as a Chaotic Sociotechnical System: Role of Information Systems in Engaging Stakeholders and Democratizing Innovation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The web is no longer simply a medium for people to exchange text. Thanks to social media (Web 2.0), it is morphing into a new socioeconomic space where e-citizen, e-democracy and crowdsourcing are becoming not only cultural paradigms, but also business drivers. Web 3.0 (the semantic web) is promising to integrate meaning, text mining, and lexical analysis into web transactions. Beyond commenting and sharing media, the upcoming Web 4.0 (some call it the intelligent web) aims to foster the realization of the knowledge society, where people harness collective intelligence to achieve not only social goals, but more importantly, codevelop knowledge products (apps or analysis tools) that can be sold in the global marketplace (Hendler and Berners-Lee 2010). In such a connected, knowledge-savvy society, a future where communities really lead decision making in urban infrastructure is not far-fetched. Empowered by apps and interactive authoring tools, communities will be able to develop project ideas (technical and nontechnical). They will also be able to analyze ideas by others and collaborate to bridge gaps and collate ideas. In such a situation, the roles (and value-added) of public officials and engineers shift from developing/presenting project ideas to communities into a realm where they work and develop tools for enabling and facilitating the self-organization of citizens’ own ideas. This paper presents a vision for the future of infrastructure development and decisionmaking in light of emerging socioeconomic and technical forces that are shaping our society—mainly the increasing desire for sustainability, globalization, e-society, and the knowledge economy. The objective of this rather hypothetical (and certainly fallible) scenario is not to predict the future. Rather, the aim is to stimulate a discussion about such a future, with specific emphasis on the role of engineers in the evolving knowledge economy. Metaphorically, in the typical mode of operation of infrastructure, the customer (the general public) delegates decision powers to public officials. Public officials retain engineers to provide professional technical services. The introduction of environmental review and community engagement (CE) legislation in the 1970s was supposed to bring some bottom-up input (views from the community) to the planning and decision-making processes. However, CE processes typically exemplified a “decide, announce, defend” mentality (Beierle 1999). Lately, the lack of suitable understanding of the needs of the web-native stakeholders contrasts with social trends and the very essence of sustainable development (where social needs are at the center). Consequently, increasing community opposition to projects have been documented in many cases with impacts on total project costs and duration. One way that cities are trying to catch up is through the use of social media tools for CE, such as crowdsourcing. For example, SeeClickFix (a Facebook-like site) is a new application that enables users in many cities to report issues with infrastructure (Nash 2009). The Canadian Broadcasting Corporation (CBC) used a virtual game along with an online news story to let readers generate and study funding options for the mushrooming infrastructure deficit (CBC 2011). As interesting as these reactive applications may be, knowledgeempowered communities are starting to develop more proactive applications. It is hypothesized that, like other issues of life, the public will want to be the direct source of all ideas—technical and nontechnical. They will want public officials and engineers to use their professional knowledge in technology and business to help them analyze and collate their own ideas, resolve conflicts, and professionally produce their ideas into a viable project. As a case in point, in 2004, the Mayor of Paris announced renovation plans for the Les Halles Garden. A local residents’ association objected due to the inadequate level of residents’ involvement. As a countereffort, they bid the design job to users of Second Life—a virtual reality/parallel world web site, where people create avatars (virtualdoubles) of themselves. As an incentive, the winning project was to receive 275,000 lindens (the e-currency of Second Life). Virtual teams from across the world worked together to develop a new design for the facility. The winning design was developed by a French group with global virtual help from Canada, China, and Germany (L’association ACCOMPLIR 2010).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it