The Category of Case in English and Albanian Nominal System: A Contrastive Analysis
Bibliographic record
Abstract
The grammatical category of case, as one of the most discussed grammatical categories in English and one of the most specific categories in Albanian, has always attracted the researchers’ attention and, therefore, there are numerous studies about this category in these two respective languages. However, the main purpose of this article is to indicate that despite their different morphological structure which implies differences in their grammatical categories, English and Albanian, also show some similarities that concern the grammatical category of case and especially the genitive case as the only marked case in English nominal system. This article examined the grammatical category of case in English and Albanian nominal system through the contrastive method, emphasizing the differences that regard several aspects of the category of case, such as the number of cases in these two languages, the way they build their case forms, the use of prepositions in building the case forms, i.e., prepositions as case markers, and also several characteristics of the category of case that these two languages have in common. The results indicate that the similarities concern mainly the genitive case. Nouns in the genitive case, in English and Albanian, share some characteristics that concern their semantic functions, their use in “the double genitive” constructions, rules of forming such constructions, and the omission of the case markers without affecting meaning.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".