Tracking the language of COVID-19 for communication: at a glance… / Profesor Madya Dr. Norwati Hj Roslim ... [et al.]
Bibliographic record
Abstract
Word of the Year 2020: Collins Dictionary has declared lockdown as the word of the year due to its sharp rise in usage during the COVID-19 pandemic (https://www.collinsdictionary.com/). Merriam-Webster’s Word of the Year for 2020 is pandemic due to its extremely high numbers of looked up in online dictionary (https://www.merriam- webster.com/). The Oxford English Dictionary (OED), however, has been unable to name its traditional Word of the Year for 2020, instead exploring how far and how quickly the language of COVID- 19 has developed in its report titled, "Words of an Unprecedented Year" (https://edition.cnn.com/). Corpus Analysis of the Language of COVID-19: The Coronavirus Corpus (Mark Davis, 2020) highlights what people are actually saying in online newspapers and magazines in 20 different English- speaking countries. This includes words and phrases such as social distancing, flatten the curve and pandemic (https://www.english-corpora.org/). A comparison between regions shows, although the word front liner is used worldwide, it is particularly frequent in South East Asia, especially the Philippines and Malaysia. Self-quarantine is more common in the US than in Canada, Great Britain, Ireland, Australia and New Zealand, where self-isolate and self- isolation are preferred. Words occurring near frontline are “frontline nurse/ medic/caregiver”, “frontline healthcare/health-care workers”, “frontline warrior/hero”, “courageous/heroic frontline workers” and “essential frontline worker” (https://public.oed.com/).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".