Bibliographic record
Abstract
This qualitative study aims at investigating the WhatsApp statuses as used by Jordanians. It also investigates the types of speech acts used in these statuses. For this purpose, the study has collected and analyzed 200 statuses. The population of the study included all English language students of Jadadra University, where the sample of the study included (50) students, representing 20 % of the whole population. The results showed that data were classified into six main topics; religious, social, political, personal, romantic and national. Additionally, five themes emerged from the data, namely, expressive, directive, assertive, commissive and declaration. Expressive speech acts represent (37 %) of the total speech acts types analyzed. The directive took the second place, representing (25%) of the total status update analyzed. The assertive and commisive fall into the third and fourth position representing (23%) and (15%) respectively. The declarative type has the no occurrences representing (0 %) of the analyzed data. Some of the recommendations suggested are that further research needs to be conducted into the speech acts used by Jordanians on different social networking platforms.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".