Designing a Literacy Program for a Better Chance, Better Community (ABC2)
Bibliographic record
Abstract
ABC2 is a 501(c)(3) nonprofit organization that connects rural communities with resources in order to trigger youth power and advocate for practical solutions and healthier lifestyles. This project concentrated on the planning stage of developing a literacy program for students in rural Halifax County. The proposal was written to take use of both sides' current strengths while also looking for ways for the organization, community, and me to expand. Its assessment entailed three steps, including evaluation of whether the project met base criteria, assessment of the project’s impact, and evaluation of the project’s complexity. The primary focus of this project was to identify the concept of followership and what it takes for an organization to gain followers. Data were gathered using a mixed methodology approach. Surveys were carried out to determine the importance of media services and the best services for the community. Additionally, ABC2 members conducted interviews to gain knowledge of the organization’s outlook, culture, infrastructure, and purpose. The findings depicted that social media and networking with neighboring school districts are used to share information, receive information, and gather information, and for promotions. The findings illustrated there is a need for a literacy program to be implemented. For the program to be implemented, brand awareness should be created and effective financial management practiced. In reflection, the project enhanced my skills in research, balancing of project schedule with expectations and contingencies, and creating an organizational budget. Additionally, it led to the evolvement of my leadership concept.
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.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".