Factors that promote Progression in Schools Functioning as a Professional Learning Community
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
The purpose of this research is to identify factors that influence the functioning of a school working as a Professional Learning Community (PLC) and to analyze the links between these factors and the school’s progression. This research was developed within the context of an interpretative research paradigm. The primary data collection tool employed is a one-hour semistructured interview with each participant, thus allowing researchers to identify each participating school’s level of development as a PLC and clarify the underlying factors that have a positive effect on this type of functioning. The interview plan, composed of themes relevant to this research project, is structured according to the Seidman model (1998). The schools were classified according to the three stages of development identified in the Professional Learning Communities Observation Grid (PLCOG) from Authors (2009a), namely the initiation, implementation, and integration stages, using the seven indicators found in the professional literature. This study suggests certain dominant factors, particularly for schools in the initiation and integration stages. Recommendations are presented to better assist school administrators in supporting their teaching staff as a PLC.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it