Bibliographic record
Abstract
The project The Impact of Information Technology in Garden Maintenance is one part of larger project entitled ‘Empowering Growth’ that partnered with the Taking Root non-profit organization to impact the lives of teenagers in juveniles detention centers. A partnership was established with the Ottawa Juvenile Detention Center (OCJDC) to build a community garden and provide recommendations of the type of Information Technology that can be used to improve gardening outcomes. The community garden will provide fresh food to supplement the detention center’s food preparation. Implementation of the garden will reduce the detention center’s food costs and allow their residents to engage in interactive activities. The aim of this project is to evaluate the integration of Information Technology into gardening and show how these technological developments influence the way farming is done and dynamically raise produce quantity for the detention center. The ‘Impact of Information Technology in Garden Maintenance’ is an assessment of the technological tools available for gardening and it proposes the development of a custom-designed garden application for the Ottawa County Detention Center (OCJDC). A project management assessment model was defined for evaluating and vetting gardening technology based on the objectives of cost, IT complexity, and quality. An assessment model was established on the following principles: Acceptance Criteria, Assumptions, Constraints, and Deliverables. To further compliment this project a web-based garden application will be developed specifically for the Ottawa County Juvenile Detention Center (OCJDC) that offers garden planning and tracking capabilities that conform to the security measures of Ottawa detention center. To evaluate the idea a prototype of the garden application was designed using “Carettas”. This prototype helped to identify specific needs of the residents and staff. The web application has functionalities useful for planning to build a garden and maintaining it during the growing season. The web application will be developed using JAVA and JSP/Servlet web technologies and will be based on the server-client model. For data persistence MySQL will be use as the Relational Database Management System (RDBMS) and Apache Tomcat as the web container to host the web application.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".