Land use ako nástroj revitalizácie krajiny: na príklade slovenskej exklávy Tardoš (Maďarsko)
Bibliographic record
Abstract
The landscape surrounding village Tardos (Tardos in Hungarian) in the north of Komarom-Esztergom County is a part of the cultural heritage of Slovaks in Hungary. The study analyses the issue of the revitalisation of the landscape in the context of its use (historical land use). Current state of the local landscape represents the result of the migration of ethnic groups to the territory of Tardos and its subsequent colonisation. Since the end of the first quarter of the 18th century the process of revitalisation of the abandoned landscape had been associated with the arrival of the Roman Catholic settlers from the counties located north of the Danube river (Nitra and Trencin). The new population began to cultivate devastated landscape of the Tardos-Tolna basin in the Gerecse Mountains. The aim of this paper is to characterize the Tardos land use with an emphasis on the period from 1725 (Slovak colonisation of the defunct village territory) to 2017. A brief assessment of the land use during the period before the arrival of the Slovak colonists is included in the study. Recent changes of areas in the analysed territory are characterized by land use classes (LUC) during the last 300 years (1725-2017) in the context of natural (geoecological) and social factors. Besides these data a framework proposal for the management of the local landscape is suggested. The development of the historical land use after the arrival of the Slovaks is outlined in the thematic maps, chart with LUC areas in particular periods and in diagram. The methodology used and the results achieved can be applied in the study of the land use of other Slovak exclaves in Tardos surroundings. Findings concerning the local land use changes with an emphasis on the period after 1725 can be possibly taken into account in practice of the creation of an integrated landscape management of the surveyed territory or in the process of consolidating the local population identity.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".