Text messaging, textese, and age differences : an exploration of fourteen consecutive undergraduate cohorts
Bibliographic record
Abstract
Text messaging is a global phenomenon characterised by a casual style of writing known as textese. The textisms which make up this digital language involve orthographic changes to letters, words, or phrases. This study builds on previous work by Kemp and Grace (2017) and investigates the textese use of Australian undergraduate students across 14 cohorts between 2009 and 2022 (N = 2501). We re-analysed previous and new data using a new personcentred scheme of creative and non-creative textisms. We also compared differences between sub-groups of younger adults aged 18 and 19 years (n= 957) and older adults aged 28 years and over (n = 598). Bayesian analyses revealed that over the 14 cohorts, the overall use of textese represented nearly a quarter of the words typed in sent messages. Generally, noncreative textisms were used more frequently than creative textisms. Across all 14 cohorts, younger adults used a higher proportion of overall textisms, creative textisms and noncreative textisms than older adults; however, there were several interactions between textism type and age over time. The use of textese over time and between age groups is interpreted in light of the various reasons people use textisms.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 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 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".