ACARA v9 CONTENT DESCRIPTION “construct arguments based on analysis of a variety of evidence to support conclusions or evaluate claims, and consider any ethical issues and cultural protocols associated with accessing, using or citing secondary data or information”
Builds on constructing arguments from a variety of cited evidence. This year the task is sharper: you evaluate a public claim, draw on several published secondary datasets, judge how good each source is, and let the conclusion follow the combined evidence. You also take real care over accessing, using and citing that evidence ethically and respectfully.
Evaluate a claim with a variety of cited evidence
A single observation can be wrong, mismeasured or too narrow. A robust scientific argument gathers several independent lines of secondary evidence, an optical orbit fit, an independent radar range, a recovered archival sky-survey image, and shows whether they point the same way. When sources collected by different observatories with different methods converge, a conclusion is far harder to dismiss. The work is to assemble that variety, judge the quality of each source, and analyse what the whole body of evidence supports, not just the one figure that suits the claim.
Evaluate the safe-passage claim from a variety of cited evidence
A public claim says a newly catalogued asteroid will pass Earth safely. A student gathers several published, cited datasets to test it. Decide which statements are sound, varied evidence that genuinely supports the conclusion.
Claim: This catalogued asteroid will pass Earth at a safe distance on its next approach.
A published optical orbit-fit dataset, cited by observatory and year, places the close approach well beyond the danger range.
An independent radar-ranging dataset from a different facility, also cited, narrows the same orbit to the same safe distance.
A recovered archival sky-survey image of the object, cited by survey and date, extends the orbit arc and confirms the prediction.
A popular video about asteroids felt reassuring, so this one must be safe too.
Figures were copied from an unnamed forum post, and only the readings that agreed were kept while the rest were dropped.
Decide whether each statement is evidence for the claim, or not.
Accessing and citing secondary data carries responsibilities
Reusing data is not the same as owning it. Before you cite a dataset you should confirm that its licence or terms allow reuse, represent the figures honestly without trimming or inflating them, and attribute the dataset, its observatory or authors and the year so a reader can reach the original. Some evidence carries stronger duties still. Where it includes Aboriginal and Torres Strait Islander knowledge, that knowledge can have cultural protocols, often described as Indigenous Cultural and Intellectual Property, governing how it may be accessed, used and cited. Treat it as belonging to its community: seek permission, attribute it correctly to the knowledge holders, present it accurately, and respect any restrictions rather than assuming it is free to take.
How should you access the Traditional Owner sky knowledge?
Some long-running observations of this part of the sky are Aboriginal and Torres Strait Islander astronomical knowledge held by a local Traditional Owner group. Choose how to use it in your argument and weigh what each choice gains and gives up.
A variety of evidence can include knowledge that belongs to people and carries cultural meaning. How you access, credit and represent it is an ethical decision as much as a scientific one.
Choose a response to see what is gained and what is given up.
Let the conclusion follow the whole body of evidence
An argument is not fixed. As you add each new cited, independent dataset, the conclusion may be reinforced, sharpened or scoped back. The honest response is to follow the variety of evidence as a whole, weighing source quality and acknowledging any source that disagrees, rather than keeping only the data that suits the claim. Step through how a safe-passage argument firms up as each properly cited dataset is added.
Watch the conclusion follow the variety of evidence
Each step adds another independent, properly cited dataset about the asteroid. See how the working conclusion is updated as the body of evidence grows.
New evidence (1 of 3)
Only a single optical orbit-fit dataset is cited, giving a wide uncertainty on the close-approach distance.
Accepted model: One cited source suggests the pass is probably safe, but the case rests on a single, uncertain orbit.
Add the next piece of evidence and watch whether the accepted model holds or has to change.
Why this matters
Whether you are advising an agency, writing a report or judging a headline, the strength of a case rests on the variety of evidence behind it and the honesty with which it is sourced. Knowing how to analyse several cited datasets, weigh their quality, credit every source, and respect the cultural protocols attached to some knowledge is a skill that reaches well beyond science class.
Quick self-check
1. To evaluate the claim that an asteroid will pass safely, you draw on a published orbit-fit table, a radar-ranging dataset and an archived photographic sky survey, each collected by different observatories. What kind of evidence is this?
2. Which version evaluates the claim using a variety of evidence, rather than resting on a single source?
3. You want to reuse figures from a published near-Earth-object dataset in your argument. Before citing it you should make sure you may access and use it by...
4. Some long-term sky observations you want to cite are Aboriginal and Torres Strait Islander astronomical knowledge held by a Traditional Owner group. The appropriate step is to...
5. One cited orbit solution disagrees with the three other sources your argument relies on. The most defensible response is to...