The Characteristics of Literacy Management in School Literacy Movement (SLM) at Junior High School in Malang - Indonesia
Bibliographic record
Abstract
This study aims to evaluate the implementation of the school literacy movement (SLM) program in junior high schools in Malang, East Java, Indonesia. The evaluation includes three stages of SLM: the stage of habituation, development, and learning. This study was an evaluative study using the CIPP model (context, input, process, and product) and used a qualitative descriptive approach. The sample unit consisted of 12 schools, with a category of nine public schools and three private schools. The schools were selected using a purposive random sampling technique. The research sample consisted of teachers, principals, and education personnel. Methods of data collection through observation, interviews, and examination of program implementation documents. Data analysis uses the Miles and Huberman model which consists of data reduction, data display, and conclusion drawing, while the formulation of strategic steps uses the calculation of internal strategic factors (IFAS) and external strategic factors (EFAS). The results showed that the implementation of new literacy at the habituation and development stage had not yet reached the learning stage. However, IFAS and EFAS values are 3.34 and 3.39, respectively. These results indicate that the development of the literacy program still has many weaknesses (<5.00) and needs intensive efforts in order to increase student literacy.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".