Social networking use and environmental engagement: the case of one million acts of green
Bibliographic record
Abstract
The increased attention to environmental issues of sustainability and green consumerism in the media has been accompanied by a rise in citizens' interest 'to do their part' for the environment. At the level of the consumer, 'going-green' has become a popular trend aimed at curbing environmental impact by using less and living in more responsible ways. To support this, there are an increasing number of content providers (e.g. web sites) that are combining green lifestyle tips, carbon calculator options, and community forums through interactive platforms. These measures are based on the belief that signing up with these sites and adopting environmentally sustainable behaviours will have positive influences on improving our environment (e.g., lowering green house gases). However, there have not been comprehensive studies to examine this proposition. Research efforts examining the ways in which networked communication and information technologies can foster environmental participation online are nascent, and there remain significant knowledge gaps as to how individual involvement with environmental initiatives can be leveraged by interactive technologies found on the web. This Major Research Paper (MRP) illustrates a case study that aimed to encourage positive environmental outcomes through online support initiatives. It assesses the influence of the Internet as a tool for engaging people in environmental issues of emissions reduction, sustainable lifestyle choices, ecologically-friendly products, and consumer responsibility in the 'going-green' marketplace. This is illustrated through a review ofliterature and a qualitative case study. Research perspectives from environmental communication, psychology and climate change (behavioural and social psychological orientation), and Internet studies (Information and communication technology (lCT), new media theory, web 2.0 (the network society) are reviewed. Further, this paper maps dimensions between these knowledge areas, discuss sites of engagement, and recommends future research questions based on the current research environment. The case study explores user motivations, barriers to participation, and member experience in Cisco-CBC's One Million Acts of Green (OMAoG) campaign. Qualitative research methods are utilized to reveal the state of environmental consciousness in participants. Focus groups and interviews were conducted with individuals and groups involved in the OMAoG campaign. This occurred during a research internship with MIT ACS Ontario, Ryerson University, and GCI Canada during the fall of2009. The purpose of this major paper is to (1) expose user experience, perceptions, and beliefs in the OMAoG campaign, (2) provide empirical insight into the functionality and impact of environmental social networking sites, and (3) lay the groundwork for more directive research on this knowledge intersection. It also offers important insight to environmental companies for engaging communities in 21st century environmentalism and improving the ways action-oriented environmental web sites function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".