Creating Cohesive Community Through Shared Reading: A Case Study of One Book Nova Scotia
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
One Book Nova Scotia is described on the program’s website as “a province-wide community reading event for adults.” Formally programmed events have included the book announcement and launch, a series of author readings, and book discussions, both face to face and through Twitter. This paper analyzes the success of the One Book Nova Scotia program in achieving its goals of developing a reading culture and community in the province of Nova Scotia based on the findings of a participant survey, distributed in both 2012 and 2013, and an analysis of the 2013 Twitter discussion. This analysis reveals that participants tended to be well-educated females, aged 50-59, and often employed in libraries, bookselling or publishing, or news media. The goal of developing or participating in a reading community was a compelling motivator for many respondents. Although many respondents indicated their desire to be part of a reading community, Twitter was not proven to be an effective forum for fostering conversation or debate related to One Book Nova Scotia. Building on the analysis, the paper concludes with some recommendations to improve the effectiveness of future programs. These recommendations include the selection of a book with strong regional connections, an expansion of publicity methods, an increase in lead time between the announcement of the book title and the start of programming, and a more strategic use of Twitter as a discussion forum. Although these recommendations arise from the specific analysis of the One Book Nova Scotia reading program, they are general enough to apply to other One Book, One Community programs.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.051 |
| Open science | 0.000 | 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