Conduct research in a particular field of knowledge

Conduct research in a particular field of knowledge — real work, not an imagined feature: named inside 4 evidenced career tasks. Below are four ready AI prompts for it, one per height of help: do it, make it easier to accept, decide when you are stuck, and change the pattern for good.

4career tasks name it
4prompt heights

The four heights

The same task, four distances: today's deadline, the next reviewer, the stuck moment, the pattern.

Execute — do the immediate task

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I have the draft research protocol for the environmental exposure study. Send the protocol with the…
I have the draft research protocol for the environmental exposure study. Send the protocol with the data management plan to Dr. Okoye in Epidemiology and to the ethics coordinator, Pablo, requesting feedback and an internal sign-off by Friday so we can begin recruitment next month. Before sending, ensure sample size and statistical assumptions match the latest pilot data and that consent language aligns with institutional policy.

Improve — make it easier to accept

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Before circulating this protocol, make it easy to approve — put the research question, primary…
Before circulating this protocol, make it easy to approve — put the research question, primary outcome and sample size rationale on page one, summarize participant burden in a short table, and flag any points the ethics board typically queries that would delay approval.

Decide — diagnose the stuck moment

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We sent the protocol draft and the stats reviewer says the sample size assumptions are optimistic…

Statistics reviewer challenged our sample size assumptions.

We sent the protocol draft and the stats reviewer says the sample size assumptions are optimistic based on the pilot variance; Dr. Okoye wants to keep timelines but ethics needs a defensible calculation. I’m afraid increasing sample size will blow the timeline and budget, but keeping it risks rejection. What likely caused the discrepancy and what is the best next move to resolve it with the stats reviewer and ethics quickly?

Become — change the pattern

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Across multiple studies we lose time because sample size calculations are revised late and consent…

Protocols repeatedly get held up by underestimated variability and unclear consent language.

Across multiple studies we lose time because sample size calculations are revised late and consent wording is rewritten after ethics review. What habit should I change when drafting protocols so statistical and ethical issues are anticipated and approvals happen faster?

Where the evidence lives

Who was seen doing this, and what people really ask.

Software tasks in the LLOS Work Atlas come from evidence, never a feature list: careers attested to do the work, real job descriptions, and the questions people actually ask (with their view counts). Facets — feature, workflow, troubleshoot, administer, deploy, scale — are open metadata: the work decides, not a taxonomy.
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The rest of the map

Same library, five ways in.