Research Article Abstracts in Two Subdisciplines of Business—Move Structure and Hedging between Management and Marketing
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
The importance of RA abstracts lies in their influence on the readers’ decision about whether the accompanying article is worth reading. A number of studies have investigated the move structure of abstracts and have generated several influential models. However, little research has been conducted on subdisciplinary variations in move structure of abstracts. Additionally, previous studies have investigated independently either the move structure or the hedging use of academic writings. The attempt of the integration of the both have been lacking yet. Therefore, this study reports the analysis of move structure and hedging use in Management and Marketing abstracts. Comparative analysis was also conducted to investigate sudisciplinary variations in both move structure and hedging use between the two subdisciplines in the field of Business. In total, sixty-four research articles abstracts published in 2012 were randomly selected form eight leading journals in two subdisciplines. Hyland’s model (2000) was adopted as analytical framework for move structure analysis, and Wordsmith Tool was used to search hedging in the corpus. Results showed that the move structure of I-P-Pr (Introduction-Purpose-Product) is the most dominant sequences in both Management and Marketing. Regarding the use of hedging, all the five types occurred in both subdisciplines of Business. The findings of this study have also demonstrated the existence of variations in terms of both move structure and the use of hedging in the abstracts between the two subdisciplines. Therefore, pedagogical implications can be proposed that teaching practices should address the variations so as to meet the specific expectations from different particular discourse communities.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it