The Intellectual Evolution of Educational Leadership Research: A Combined Bibliometric and Thematic Analysis Using SciMAT
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
This study aims to describe the century-long trajectory of educational leadership research (ELR), including changes over time in its main and subsidiary themes, as well as its most influential authors, papers, and journals. The study combines the bibliometric performance and science mapping analysis of 7282 articles retrieved from the Scopus and WoS databases. SciMAT software (version 1.1.04) was used to analyze changes over four sequential time periods and to exhibit the thematic evolution of the field—Period 1 (1907 to 2004), Period 2 (2005 to 2012), Period 3 (2013 to 2019), and Period 4 (2020–2023). Research during Period 1 focused on principals and included efforts to distinguish between their administrative functions and forms of ‘strong’ leadership contributing to school improvement. Period 2 included research aimed at understanding what strong principal leadership entailed, including the development and testing of more coherent models of such leadership. While instructional and transformational leadership models were prominent during Periods 1 and 2, Period 3 research invested heavily in conceptions of leadership distribution. Early research about ‘social justice leadership’ appeared during this period and eventually flourished during Period 4. While principals were an active focus through all Periods, the leadership of others gradually dominated ELR and accounted for the broader leadership theme found in all four periods. The results point to the evolutionary nature of ELR development, which eventually produced a relatively robust knowledge base. Experiences with the COVID-19 pandemic suggest that crises such as this might prompt more revolutionary orientations in the ELR field.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.019 | 0.082 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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