FROM STATE SUPERVISION TO INTERNATIONALIZED AND TECHNOLOGY-DRIVEN EDUCATION
Bibliographic record
Abstract
This paper examines the evolution of education from a state-supervised model to an internationalized and technology-driven educational reality. With a focus on exploring how educational reforms impact social justice, the study analyzes the function of education as a tool for reproducing social inequalities. It investigates the influence of internationalization and technology on educational policies, as well as the management of education systems, while exploring how contemporary reforms shape school operations and the educational process in a global environment. Emphasis is placed on the transition from state supervision, where educational policies and decisions were primarily national and local, toward a system increasingly guided by international organizations such as the OECD, economic actors, and technological advancements. Through a critical analysis of international educational policies and their impact on national education systems, along with a literature review and an examination of shifts in goal-setting processes and the orientation of educational practices, the paper highlights the role of technology and globalization in reshaping the educational landscape. It also considers the changing relationships between states and educational institutions, as well as the influence of economic and political factors in shaping modern educational strategies. Despite the opportunities that technology offers for enhancing education, the research suggests that the trend toward internationalized and technology-driven education may exacerbate inequalities between countries and educational systems while limiting local and national autonomy.
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 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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".