Bibliographic record
Abstract
This dissertation explores a model of social change which I have labeled "dialogic."Each of the three cases I have chosen for this study has been included because I believe that the design of each intervention departs significantly and creatively from traditional, less Other-oriented, social change efforts.Dialogic social change begins with the assumption that human beings cannot be developed, modernized, or empowered by external parties.Instead, this conception of change is guided by the assumption that individuals are autonomous, trustworthy beings who are capable of deciding when to engage with new ideas and opportunities for action.First, I analyze the strategic communication of the "Billionaires for Bush," a group of playful and ironic protesters, most active in New York City preceding the 2004 U.S. Presidential election.In this case I focus on the ability of the Billionaires to creatively inspire and invite civic participation, which resulted in the self-organization of more than 70 "spin off" Billionaires for Bush chapters.The second case I examine is "Scenarios from Africa," an HIV/AIDS-related communication process in Senegal centered on a script writing contest for young people implemented voluntarily by a vast network of community based organizations.I discuss how the contest promotes youth agency in Senegal, allowing contest participants to shift from their traditional role as targets of information campaigns to instead become creators of HIV prevention content.Finally, I present the "invitational" Cultura Ciudadana (civic culture) communication strategy employed by Antanas Mockus, the former mayor of Professors at New York University who believed in me, got me excited about research and assured me that I had "what it takes" to pursue a doctorate.I thank Arvind Singhal for proving that it is possible to write academic books that have photos, drawings and stories.I also thank him for a well timed "Mother Teresa story," from which I learned that there is a difference between being anti-war and being pro-peace.I am very grateful to Bill Rawlins for his support and encouragement, and especially for writing "Rock on!" in the margins of my earliest papers as a Doctoral student.His love of dialogic theory was contagious and I am grateful to him for exposing me to the writings of Martin Buber, Mikhail Bakhtin and Gregory Bateson.I thank Rafael Obregon for introducing me to two new worlds; Colombia and the world of Latin American communication theory.Rafael has been a constant supporter and a source of inspiration through his work and writing on social change.I thank Greg Shepherd for introducing me to the Pragmatists and for fanning the flames of my belief in community and in meliorism.I also appreciate the careful attention Greg paid to my writing and the word choices I have made; his feedback and encouragement led to much improved and expanded chapters.I thank Devika Chawla who has more-than-generously supported and mentored me since my first year at Ohio University.Devika has helped me become a better writer and she has taught me just about everything I currently know about academic life.Devika Chawla and Ani Ruhil have been a constant source of vi support, guidance, and (no small detail), hot and delicious meals when I most needed them.I am extremely grateful to various individuals and institutions on the Ohio
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.050 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".