Evidence · Intermediate · About 4 min
Separate facts from predictions
Facts, predictions and values need different support
Both sides · Constructive speechRead the case: The four-day workweek
Resolution A four-day, 32-hour standard work week should replace the current five-day, 40-hour model
24 volunteer workplaces, covering offices, retail and distribution, joined a six-month comparison.
- Half were assigned by lottery to 32 hours at unchanged weekly pay; half kept 40 hours.
- Both groups maintained an output index of 100.
- Absence averaged three days per worker in the shorter-week group and five in the comparison group; these counts were not adjusted for scheduled days.
- Customer coverage was maintained, but payroll in the shorter-week retail and distribution sites was 8% higher; office payroll was unchanged.
- Healthcare and other continuous-service industries were not included.
For this practice round, the affirmative defends replacing the normal 40-hour model with a 32-hour standard at unchanged weekly pay; it does not claim every shift must be identical. The negative challenges whether the benefits justify the costs of that replacement.
A fact is what happened. A prediction is what you think will happen. A value is what you think should matter most. Most constructives use all three, and each needs a different kind of support.
Knowing which is which shows you where the real clash is. A study can prove a fact and leave the prediction wide open. A value needs reasons, and no statistic can tell the audience what to care about.
The shorter-week group maintained output at unchanged weekly pay.
A fact: what the study recorded.
Other workplaces with similar tasks and coverage arrangements could also deliver a time gain without losing output.
A prediction: similar workplaces will likely see similar results. It needs a reason, not just the fact.
Workers’ usable time deserves weight when choosing the normal workweek.
A value: time matters. It needs its own argument for why it outweighs the cost.
State the fact
Say what was recorded and how far it reaches.
Argue the prediction
Explain why the result would happen elsewhere, and under what conditions.
Defend the value
Give a reason this consequence should matter most.
Three claims in the same case
Resolution A four-day, 32-hour standard work week should replace the current five-day, 40-hour model
24 volunteer workplaces, covering offices, retail and distribution, joined a six-month comparison.
- Half were assigned by lottery to 32 hours at unchanged weekly pay; half kept 40 hours.
- Both groups maintained an output index of 100.
- Absence averaged three days per worker in the shorter-week group and five in the comparison group; these counts were not adjusted for scheduled days.
- Customer coverage was maintained, but payroll in the shorter-week retail and distribution sites was 8% higher; office payroll was unchanged.
- Healthcare and other continuous-service industries were not included.
For this practice round, the affirmative defends replacing the normal 40-hour model with a 32-hour standard at unchanged weekly pay; it does not claim every shift must be identical. The negative challenges whether the benefits justify the costs of that replacement.
- Observation
The shorter-week group maintained output at unchanged weekly pay.
A fact: what the study recorded.
- Affirmative · Prediction
Other workplaces with similar tasks and coverage arrangements could also deliver a time gain without losing output.
A prediction: similar workplaces will likely see similar results. It needs a reason, not just the fact.
- Affirmative · Priority
Workers’ usable time deserves weight when choosing the normal workweek.
A value: time matters. It needs its own argument for why it outweighs the cost.
Figure out whether the other side is fighting the fact, the prediction or the value.
Test the reasoning
Read the practice case
Resolution A four-day, 32-hour standard work week should replace the current five-day, 40-hour model
24 volunteer workplaces, covering offices, retail and distribution, joined a six-month comparison.
- Half were assigned by lottery to 32 hours at unchanged weekly pay; half kept 40 hours.
- Both groups maintained an output index of 100.
- Absence averaged three days per worker in the shorter-week group and five in the comparison group; these counts were not adjusted for scheduled days.
- Customer coverage was maintained, but payroll in the shorter-week retail and distribution sites was 8% higher; office payroll was unchanged.
- Healthcare and other continuous-service industries were not included.
For this practice round, the affirmative defends replacing the normal 40-hour model with a 32-hour standard at unchanged weekly pay; it does not claim every shift must be identical. The negative challenges whether the benefits justify the costs of that replacement.
Your turn
Affirmative · Constructive speechWrite an observation, a forecast with a mechanism and a priority supporting the affirmative. Keep the broader prediction distinct from the review.
Read the case: AI and the future of work
Resolution Advanced AI will on net improve outcomes for workers
a two-year review of 30 employers records 300 retained workers receiving 4% higher inflation-adjusted pay and working 37 rather than 40 hours per week after AI adoption.
- Sixty entry-level roles were removed and 40 technical roles added.
- Of the 60 displaced workers, 18 entered the new roles, 24 found work elsewhere at 8% lower pay, and 18 were still unemployed six months later.
- The other 22 new roles went to different applicants.
- The review does not isolate AI from every other change or forecast the whole economy.
The affirmative argues that productive tools can improve pay and time for many workers. The negative argues that concentrated losses and barriers to new work can outweigh those gains.
You can type or use your keyboard’s microphone to dictate. Your text stays editable. Practice is optional.
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Observed: … I predict… because… This matters because…
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Use the timer for a spoken attempt if it helps. Practice without recording, then note what you would improve.
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Resolution Advanced AI will on net improve outcomes for workers
Read the practice task and case
Write an observation, a forecast with a mechanism and a priority supporting the affirmative. Keep the broader prediction distinct from the review.
a two-year review of 30 employers records 300 retained workers receiving 4% higher inflation-adjusted pay and working 37 rather than 40 hours per week after AI adoption.
- Sixty entry-level roles were removed and 40 technical roles added.
- Of the 60 displaced workers, 18 entered the new roles, 24 found work elsewhere at 8% lower pay, and 18 were still unemployed six months later.
- The other 22 new roles went to different applicants.
- The review does not isolate AI from every other change or forecast the whole economy.
The affirmative argues that productive tools can improve pay and time for many workers. The negative argues that concentrated losses and barriers to new work can outweigh those gains.
Your response
You can return to the practice whenever you want.
One model response
Observed: 300 retained workers gained real pay and worked fewer weekly hours. I predict further worker benefits where productive tools let the same work be done in less time and workers share that value through pay or hours. This matters because income and usable time improve working lives. The review supports that possible pathway; defending the overall forecast also requires comparing displacement and explaining how widely workers are likely to share the gains.
This is the outcome recorded for the retained group.
This explains a route from productive tools to a possible time gain.
This gives the consequence a reason to carry weight.
The forecast names a mechanism and a distribution condition instead of disguising the observation as proof of the whole future. The priority explains why the measured outcomes matter.
Review the performance
- ArgumentsI distinguish the three claim types.
- EvidenceI give the forecast a mechanism and relevant conditions.
- ClarityI explain why the priority matters.
Choose one move to improve, revise your response, then try it aloud.
Common mistakes to avoid
- Presenting a prediction as if it were already measured.
- Acting like a value cannot be argued for.
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