Bibliographic record
Abstract
The purpose of this study is to investigate the relationship between the quotative be+like and historical present (HP). The use of be+like to introduce Direct Speech (DS) emerged some decades ago, and since then, has developed particularly among young English speakers. In addition to the sociolinguistic perspective (e.g., gender difference), the form of be+like in narrative has been researched. Although previous research has shown that be+like is frequently used in HP, it is unclear whether the frequency depends on region (e.g., New York area), affiliation (e.g., university), or English variants (e.g., Canadian English). Therefore, this research used a large-scale American English corpus to investigate whether this is a general tendency. The results indicate that many uses of be+like also appear in HP in the large-scale corpus, suggesting that the link between the quotative be+like and HP is common in spoken American English and across English variants. The research also provides several examples of be+like in HP from the corpus. It is observed that HP used in the quotative be+like can have a distinct function from those claimed in the literature, namely highlighting an important event by switching tenses, characterization of people in the narrative, and the accuracy of reported speech.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 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".