547 Systematic review evidence in one minute or less
Bibliographic record
Abstract
<h3>Introduction</h3> Getting research evidence to knowledge users is a challenge. The Institute for Work and Health (IWH) initiated a systematic review program in 2004 to synthesise scientific literature on prevention of workplace injuries and disability. IWH systematic review products include 2–3 page lay summaries (called Sharing Best Evidence). The lay summaries are popular but are considered long by some knowledge users. Our objective was to produce and post short videos that summarise key findings of systematic reviews in one minute or less. <h3>Methods</h3> Video shorts are created by a multi-disciplinary team including a researcher, a video producer and a communications expert. The video shorts are based on high quality research (e.g. systematic review findings). Key messages are created in consultation with stakeholders. The production process begins with a storyboard (frame-by-frame outline). Development requires careful attention to style, pacing, tone, clarity, visual interest and audience appeal. Videos are tested with members of the target audience before being posted. Video shorts typically take about four weeks to complete. <h3>Results</h3> Two, 1 min videos were developed by IWH made to reach busy stakeholders with evidence they need in their work. The first video, posted since October 2016, is popular receiving over 1100 hits to date. Length: Videos are kept as short as possible, less than one minute. Format: No voice-overs are used. Simple graphics, images, text and short video clips are used, with instrumental background music. Content: Key messages from research findings are delivered in brief snippets of text. <h3>Conclusion</h3> Our videos are designed to serve two purposes: provide viewers with key evidence they can use, and link the viewer to the IWH website where they can read more information. Consultations with stakeholders on the key messages are important. One-minute research video shorts are an effective means of disseminating key research findings.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| grok | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| opus | MetaresearchScholarly communication Domain: Reporting · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.202 | 0.189 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.044 | 0.035 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".