Digitizing Government Relations: Increasing Community Amongst Advocates with Electronic Advocacy Tools to Enhance Lobbying
Bibliographic record
Abstract
This study examined participation in online advocacy portals for government relations purposes and studied the related propensity to take political action by participants. In addition, this study examined opinion formation regarding political leaders and issues informed by portal participation. This study undertakes to answer a number of questions aimed at determining if advocacy organizations are well served by using these tools as part of their government relations programs. An online email survey was sent to all portal users of www.workersbuildcanada.ca, an online advocacy portal operated by Canada’s Building Trades Unions to augment traditional government relations activities. Participation in an online portal increases propensity of advocates to take political action overall and helps to shape opinion on political issues and elected officials for the users. Advocates also experience an increased sense of connectedness to other members of the portal creating an increased sense of community. There are important evidenced differences in the voting and political behaviours of advocates based on partisan attachment levels. Those who identify as politically partisan are more likely to take political action in an online advocacy portal than those who identify as not politically attached. This partisan split also revealed differing levels of perceived importance placed on values and traits sought in elected officials. Member based organizations can improve overall satisfaction levels and feelings of connectedness of members to the organization by offering these kinds of advocacy tools. Organizations should make these tools available to identified partisan supporters to optimize participation in lobbying activities.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".