Chapter 5 — Privacy and data protection: tools and interpretation
Lesson map
Lesson 05 published. Map, example, EX021.
flowchart TD
N0["Learning outcomes"]
N1["5.1 Practical tools"]
N2["5.2 Reading results"]
N3["5.3 Uncertainty"]
N4["5.4 Avoiding overstatement"]
N0 --> N1 --> N2 --> N3 --> N4
N4 --> EX["Worked example"]
EX --> Q["Exercise EX021"]
Logical drawing
flowchart LR
N0["Learning outcomes"]
N1["5.1 Practical tools"]
N2["5.2 Reading results"]
N3["5.3 Uncertainty"]
N4["5.4 Avoiding overstatement"]
N0 --> N1 --> N2 --> N3 --> N4 --> Q["EX021"]
[Learning outcomes]
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v
[5.1 Practical tools]
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v
[5.2 Reading results]
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v
[5.3 Uncertainty]
|
v
[5.4 Avoiding overstatement]
|
v
[Worked example] --> [Exercise EX021]
Learning outcomes
You will (1) use simple tools to examine data and settings; (2) interpret results carefully; (3) avoid overstating findings.
5.1 Practical tools
Marta uses the recruitment system's built-in reports, spreadsheet filters on synthetic exports, the email system's search for attachments sent externally, and short Python scripts written with Ms. Lin's help. She learns to start with the system's own reporting before exporting data, because every export creates a new copy that must be protected and deleted. When she needs an export, she asks for only the fields needed for her question, such as last contact date and pool status, not full profiles. Fewer fields mean less risk.
5.2 Reading results
A report shows that 340 emails with CV attachments were sent to external addresses last month. Marta resists concluding that 340 CVs were shared improperly. Most went to client employers as part of normal shortlisting. She samples twenty and checks whether each candidate agreed to be put forward for that client. Seventeen did, two cannot be confirmed and one went to a consultant's personal email address. Her interpretation is that the main issue is undocumented candidate agreement, plus one serious personal email case. Context shapes interpretation.
5.3 Uncertainty
Ms. Lin teaches Marta to state what a result does and does not show. The sample of twenty suggests that undocumented agreement affects a minority of cases, but it cannot give a precise rate for the whole month. The personal email case shows that it happens, not how often. Marta writes her findings with phrases such as in the sample and could not be confirmed, which help managers understand the strength of the evidence and avoid either panic or complacency. Precision builds trust.
5.4 Avoiding overstatement
Marta's first draft says Halden routinely shares CVs without consent. Ms. Lin asks whether the evidence supports routinely. Marta rewrites it: in a sample of twenty external CV emails, two lacked a recorded agreement and one went to a personal address. The revised wording is less dramatic but more credible, and the managing director acts on it immediately. Marta notes that overstatement damages trust in privacy advice, especially when managers later check the evidence for themselves. The facts were serious enough without exaggeration.
Worked example
Marta uses built-in reports and minimal exports, samples twenty of 340 external CV emails, finds two unconfirmed agreements and one personal-address case, and rewrites findings to match the evidence.
Synthetic case. Results are synthetic.
Errors and limits
Samples show patterns, not exact rates; say so.
Exercises
- EX021 — Start with reports. Why start with built-in reports? Rubric: 3 = exports create new copies;; 2 = mentions copies;; 1 = vague;; 0 = none.
- EX022 — Sample result. What did the sample of twenty show? Rubric: 3 = 17 agreed, 2 unconfirmed, 1 personal email;; 2 = most;; 1 = one;; 0 = none.
- EX023 — Main issue. What was the main issue identified? Rubric: 3 = undocumented candidate agreement;; 2 = partly correct;; 1 = vague;; 0 = none.
- EX024 — Careful phrase. Give a phrase that signals uncertainty. Rubric: 3 = in the sample; could not be confirmed;; 2 = one;; 1 = vague;; 0 = none.
- EX025 — Overstatement. Which word did Ms. Lin challenge? Rubric: 3 = routinely;; 2 = partly correct;; 1 = other;; 0 = none.
Continue studying — lesson 05 (chapter 05 of 12)
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