Introduction to Social Research Methodology

Research goals and research questions

Ben Stanley

Department of Social Sciences, SWPS University

October 20, 2026

Course outline

Course outline: session 2 (today) Course outline: 15 stations. 1 — Nature and purpose of social research (done); 2 — Research goals and research questions (today); 3 — Hypotheses and research design (to come); 4 — Research ethics (to come); 5 — Conducting a literature review (to come); 6 — Secondary data analysis (to come); 7 — Qualitative approaches (to come); 8 — Quantitative approaches and measurement (to come); 9 — Mixed methods research (to come); 10 — Sampling and participant recruitment (to come); 11 — Questionnaire design and survey fieldwork (to come); 12 — Interviews and focus groups (to come); 13 — Quantitative data analysis (to come); 14 — Qualitative data analysis (to come); 15 — Reporting research; course review (to come). 1 Nature and purpose of social research 2 Research goals and research questions TODAY 3 Hypotheses and research design 4 Research ethics 5 Conducting a literature review 6 Secondary data analysis 7 Qualitative approaches 8 Quantitative approaches and measurement 9 Mixed methods research 10 Sampling and participant recruitment 11 Questionnaire design and survey fieldwork 12 Interviews and focus groups 13 Quantitative data analysis 14 Qualitative data analysis 15 Reporting research; course review

Today’s lecture

  • From problems to topics — how a managerial problem becomes a researchable topic, and how to get its scope right
  • Research goals — the three purposes a study can serve: exploration, description, explanation
  • From topic to question — turning a topic into a question that a study can actually answer
  • Criteria and flaws — what a sound research question looks like, and the ways questions most often go wrong
  • By the end, you should be able to take a vague organisational worry and turn it into a question worth researching

From managerial problems to research topics

The managerial problem

  • Meet Meridian: a mid-sized Polish retail-and-services company — around 450 employees, 32 stores, and a growing e-commerce arm
  • In two years, annual staff turnover has risen from 14% to 27%, and customer satisfaction scores are falling
  • The board wants evidence, not hunches — and you are the junior research team advising it
  • Notice what the board has actually given you: not a research question but a problem — a gap between how things are and how it wants them to be
  • The work of this session is the journey from that problem to a question research can answer

Where do research topics come from?

  • The key process is turning an idea or general concern into a topic that can become a research problem
  • Don’t begin by asking “what shall I write about?” — ask “what do I want to understand or learn about?”
  • Sources of topics include:
    • Practical problems — a turnover spike, a falling satisfaction score, a failing product
    • Existing research — course readings, journals, and studies that leave questions open
    • Your own prior work — written work or projects you have already undertaken
    • Received wisdom — “common sense” claims circulating in the media or the organisation that nobody has tested systematically
  • In organisations, the richest source is the gap between what people believe and what has actually been checked

What makes a good research topic?

  • Before committing to a topic, ask five hard questions of it:
    • Will anyone care about the answer? — relevance to the organisation or to knowledge
    • Is the problem solvable in the time available? — a semester, not a career
    • Will I add something new? — or has the question already been answered well
    • Do I have good tools to address it? — methods, skills, and data within reach
    • What makes me think I will succeed? — an honest audit of your resources
  • These questions echo last week’s three criteria — relevance, feasibility, ethics — but sharpen them into a working checklist

Running example: “why are people leaving Meridian?” passes easily — the board cares, data and staff are accessible, and a semester is enough to make real progress.

Getting the scope right

Getting the scope of a research topic right A spectrum from broader to narrower, with the right scope in the middle. Too broad, a field, for example employee motivation, organisational culture or customer behaviour: too many sources, so nothing can be included, excluded or prioritised; too general, so no framework for the problem emerges; too many ideas to integrate into one study. Too narrow, an incident whose significance is limited to a tiny, unique population: not enough information, and what there is is tangential; too specific to support significant conclusions; nothing generalises to other contexts. The right scope is focused and time-limited: a defined outcome, group and setting, with something left to investigate; broad enough that the answer matters beyond the case, narrow enough that you can actually deliver it. Running example: staff turnover is still a field; why front-line store staff leave Meridian is the right scope; why the Saturday shift at store 17 resigned in March is an incident. the right scope broader narrower Too broad: a field e.g. employee motivation, organisational culture, customer behaviour Too many sources: nothing to include, exclude or prioritise Too general: no framework for the problem emerges Too many ideas to integrate into one study Too narrow: an incident significance limited to a tiny, unique population Not enough information, and what there is is tangential Too specific to support significant conclusions Nothing generalises to other contexts Focused, time-limited a defined outcome, group and setting — with something left to investigate Broad enough that the answer matters beyond the case; narrow enough that you can actually deliver it. RUNNING EXAMPLE “Staff turnover”: still a field RUNNING EXAMPLE “Why front-line store staff leave Meridian” RUNNING EXAMPLE “Why did the Saturday shift at store 17 resign in March?”

Narrowing a topic: six strategies

Six strategies for narrowing a research topic, applied to Meridian Six cards in two rows. The first three slice the subject matter; the last three bound the coverage. Aspect, one lens, or one facet: not turnover at Meridian, but the role of line management in turnover. Components, smaller parts of the unit: not employees, but sales staff with under two years' tenure. Type, one class of people or events: not all departures, but voluntary resignations only. Place, a smaller unit: not all 32 stores, but the five stores with the highest turnover. Time, a shorter period: not in recent years, but since the e-commerce expansion began. Relationship, how two things relate: not what is going on with morale?, but how does perceived workload relate to intention to quit?. Slice the subject matter Bound the coverage Aspect one lens, or one facet NOT “turnover at Meridian” BUT “the role of line management in turnover” Components smaller parts of the unit NOT “employees” BUT “sales staff with under two years' tenure” Type one class of people or events NOT “all departures” BUT “voluntary resignations only” Place a smaller unit NOT “all 32 stores” BUT “the five stores with the highest turnover” Time a shorter period NOT “in recent years” BUT “since the e-commerce expansion began” Relationship how two things relate NOT “what is going on with morale?” BUT “how does perceived workload relate to intention to quit?”

Research practicalities

  • A topic must also survive contact with practical reality:
    • Can you physically access the object of your research?
    • Are there gatekeepers who can grant or deny access — and will they?
    • Will there be political or administrative obstacles?
    • Can you actually reach the people you need to survey, interview, or observe?
    • Do you have the language skills you need?
    • If using existing documents or data, can you actually get at the materials?
  • Ultimately, a good research topic is one you can investigate with the resources you have available

Running example: studying Meridian’s staff needs the board’s blessing — but studying its competitors’ staff would founder on access, however interesting the comparison.

Research goals

Three goals of research

The three goals of research compared Three columns, one per goal. Exploration: asks What could be going on here? Appropriate when the phenomenon is new, poorly understood or surprising. Typically small, open-ended: conversations, open interviews, observation. Output: a better set of questions. Running example: open exit conversations with recent leavers Description: asks What, who, where, how many, how often? Appropriate when you need the pattern measured precisely and systematically. Typically careful measurement of a population or situation. Output: the foundation: where the problem lives. Running example: which stores, roles and tenure groups lose most staff? Explanation: asks Why? Appropriate when description has established a pattern worth explaining. Typically relating variables: does X influence Y, and how?. Output: causes, which are levers to pull. Running example: does perceived workload explain why sales staff resign? 1 Exploration What could be going on here? WHEN the phenomenon is new, poorly understood or surprising TYPICALLY small, open-ended: conversations, open interviews, observation OUTPUT a better set of questions RUNNING EXAMPLE open exit conversations with recent leavers 2 Description What, who, where, how many, how often? WHEN you need the pattern measured precisely and systematically TYPICALLY careful measurement of a population or situation OUTPUT the foundation: where the problem lives RUNNING EXAMPLE which stores, roles and tenure groups lose most staff? 3 Explanation Why? WHEN description has established a pattern worth explaining TYPICALLY relating variables: does X influence Y, and how? OUTPUT causes, which are levers to pull RUNNING EXAMPLE does perceived workload explain why sales staff resign?

Goals combine and sequence

The three goals combined in sequence Three chevrons in order: explore, to find out what might matter; describe, to establish the pattern precisely; explain, to test why the pattern holds. Running example: exit conversations, then a turnover audit, then a test of the workload hypothesis. Underneath: every study should know its primary goal, because that is what disciplines the design. Two failure modes: an exploratory study dressed up as explanation over-claims, since twenty exit interviews cannot show that workload causes turnover; an explanatory question tackled with exploratory tools under-delivers, since an open chat with whoever is available will not settle it. Explore to find out what might matter Describe to establish the pattern precisely Explain to test why the pattern holds RUNNING EXAMPLE RUNNING EXAMPLE RUNNING EXAMPLE exit conversations a turnover audit a test of the workload hypothesis Every study should know its primary goal: that is what disciplines the design. OVER-CLAIMS An exploratory study dressed up as explanation: twenty exit interviews cannot show that workload causes turnover. UNDER-DELIVERS An explanatory question tackled with exploratory tools: an open chat with whoever is available will not settle it.

From topic to research question

Why research questions matter

  • A topic tells you what territory you are in; a research question tells you what, exactly, you must find out
  • The research question does three jobs at once:
    • Guides the research — every later decision refers back to it
    • Determines the scope — it fixes what is inside and outside the study
    • Shapes the methodology — the wording of the question points toward the methods that can answer it
  • A study without a clear question drifts: data get collected because they are available, not because they are needed
  • The question is the heart of the study — everything else is anatomy around it

Types of research question

Type Asks Goal served
Descriptive What is happening? How much? How often? Description
Comparative How do A and B differ? Description
Explanatory Why is X happening? Does X affect Y? Explanation
Exploratory What could be going on here? What might matter? Exploration

Matching question to goal: Meridian

One Meridian topic, four research questions One topic, voluntary resignations at Meridian, branches into four questions, each serving a different goal and calling for different evidence. Exploratory: What do departing employees say about their reasons for leaving Meridian? Evidence: open exit conversations. Descriptive: How does voluntary turnover vary across Meridian's stores, roles and tenure bands? Evidence: HR records, measured across the company. Comparative: Do turnover rates differ between Meridian's stores and its e-commerce arm? Evidence: the same measure in two parts of the business. Explanatory: Does perceived workload affect front-line employees' intention to quit? Evidence: workload and intention to quit, related. ONE TOPIC Voluntary resignations at Meridian EXPLORATORY What do departing employees say about their reasons for leaving Meridian? evidence: open exit conversations DESCRIPTIVE How does voluntary turnover vary across Meridian's stores, roles and tenure bands? evidence: HR records, measured across the company COMPARATIVE Do turnover rates differ between Meridian's stores and its e-commerce arm? evidence: the same measure in two parts of the business EXPLANATORY Does perceived workload affect front-line employees' intention to quit? evidence: workload and intention to quit, related

Managerial question ≠ research question

Managerial questions and research questions The managerial question, how do we stop people leaving, is a demand for a decision. Broken down, it becomes research questions, demands for knowledge: who leaves, why do they leave, what would retain them. Their answers inform the decision, which also weighs costs, values and strategy, things research informs but cannot settle. The same issue both ways: should we raise pay is a decision; would a pay rise reduce resignations more than a workload reduction is a research question. In practice, the research team's first deliverable to the board is not data but the board's worry translated into three or four researchable questions. MANAGERIAL QUESTION “How do we stop people leaving?” a demand for a decision break it down Who leaves? Why do they leave? What would retain them? research questions: demands for knowledge answers inform THE DECISION also weighs costs, values and strategy, which research informs but cannot settle The same issue, both ways A DECISION “Should we raise pay?” A RESEARCH QUESTION “Would a pay rise reduce resignations more than a workload reduction?” IN PRACTICE The research team's first deliverable to the board is not data: it is the board's worry translated into three or four researchable questions.

Criteria and common flaws

What makes a sound research question?

Four tests a sound research question must pass A question passes through four gates in turn before it counts as a sound research question. 1, Answerable: Could evidence settle it? Can you say what data would count as an answer? 2, Focused: Does it ask one thing, about a defined population, place and period? 3, Feasible: With the time, access, skills and resources you actually have? 4, Non-trivial: Is the answer genuinely unknown? Does someone learn something? The sharpest single test: can I describe the evidence that would answer this question, and could that evidence realistically be gathered? Textbooks add clear and concise, researchable, relevant and significant, specific, and original: the same virtues from other angles. a question 1 Answerable Could evidence settle it? Can you say what data would count as an answer? 2 Focused Does it ask one thing, about a defined population, place and period? 3 Feasible With the time, access, skills and resources you actually have? 4 Non-trivial Is the answer genuinely unknown? Does someone learn something? a sound question THE SHARPEST SINGLE TEST Can I describe the evidence that would answer this question — and could that evidence realistically be gathered? Textbooks add: clear and concise · researchable · relevant and significant · specific · original — the same virtues from other angles

Flaw: too broad, and unanswerable

Flawed research questions and their repairs: too broad and unanswerable Two flaws side by side, each with its definition, a flawed example, why it fails, and the repair. Too broad: The question covers a field, not a study. Example: What affects employee motivation? Every study ever written is relevant; none is decisive. Repair: Narrow by aspect, component, type, place, time or relationship. Unanswerable: No evidence could settle it, even in principle. Example: Would turnover have stayed at 14% without the e-commerce expansion? What is the true character of our company culture? A counterfactual with no comparison; an essentialist question. Repair: Rebuild around something observable: a comparison, a measurable outcome, a defined population. TOO BROAD The question covers a field, not a study. ✗ “What affects employee motivation?” Every study ever written is relevant; none is decisive. REPAIR Narrow by aspect, component, type, place, time or relationship. UNANSWERABLE No evidence could settle it, even in principle. ✗ “Would turnover have stayed at 14% without the e-commerce expansion?” ✗ “What is the true character of our company culture?” A counterfactual with no comparison; an essentialist question. REPAIR Rebuild around something observable: a comparison, a measurable outcome, a defined population.

Flaw: double-barrelled, and leading

Flawed research questions and their repairs: double-barrelled and leading Two flaws side by side, each with its definition, a flawed example, why it fails, and the repair. Double-barrelled: One question smuggles in two, which may have different answers. Example: How satisfied are employees with their pay and their line managers? Satisfied with one, furious with the other: what is the answer? Repair: Split it, and ask each question separately. Leading: The question presupposes the answer to the very thing at issue. Example: Why do Meridian's store managers neglect their staff? Perhaps they don't: the question has already convicted them. Repair: Remove the presupposition: first ask whether, then ask why. Both flaws recur in questionnaire wording, so spotting them now pays off again when we design surveys. DOUBLE-BARRELLED One question smuggles in two, which may have different answers. ✗ “How satisfied are employees with their pay and their line managers?” Satisfied with one, furious with the other: what is the answer? REPAIR Split it, and ask each question separately. LEADING The question presupposes the answer to the very thing at issue. ✗ “Why do Meridian's store managers neglect their staff?” Perhaps they don't: the question has already convicted them. REPAIR Remove the presupposition: first ask whether, then ask why. Both flaws recur in questionnaire wording, so spotting them now pays off again when we design surveys.

Flaw: value-laden, and trivial

Flawed research questions and their repairs: value-laden and trivial Two flaws side by side, each with its definition, a flawed example, why it fails, and the repair. Value-laden: It asks for a moral verdict, not an empirical finding. Example: Is it acceptable for Meridian to monitor employees' screen activity? No data collection can settle what is acceptable. Repair: Research the empirical parts — what monitoring does to trust, stress and performance — and leave the verdict to deliberation. Trivial: Answerable, focused, feasible… and worthless. Example: Do employees prefer being paid on time to being paid late? We know; nothing is learned. Repair: Find the version of the question whose answer is genuinely uncertain. The asymmetry: value-laden questions ask too much of research; trivial ones ask too little. VALUE-LADEN It asks for a moral verdict, not an empirical finding. ✗ “Is it acceptable for Meridian to monitor employees' screen activity?” No data collection can settle what is acceptable. REPAIR Research the empirical parts — what monitoring does to trust, stress and performance — and leave the verdict to deliberation. TRIVIAL Answerable, focused, feasible… and worthless. ✗ “Do employees prefer being paid on time to being paid late?” We know; nothing is learned. REPAIR Find the version of the question whose answer is genuinely uncertain. The asymmetry: value-laden questions ask too much of research; trivial ones ask too little.

Flaw: not researchable, and prediction without mechanism

Flawed research questions and their repairs: not researchable and prediction without mechanism Two flaws side by side, each with its definition, a flawed example, why it fails, and the repair. Not researchable: A decision or policy question posed as if it were empirical. Example: Should Meridian close its five worst-performing stores? “Should” mixes evidence with strategy, cost and values. Repair: Extract the researchable core: what share of those stores' underperformance is explained by local factors that closure would not fix? Prediction without mechanism: A bare forecast with no explanatory content. Example: Will customer satisfaction improve next year? Whatever happens, you learn nothing about why — so nothing transfers. Repair: Anchor it in a mechanism: does delivery speed drive satisfaction, so that this year's logistics investment should raise next year's scores? NOT RESEARCHABLE A decision or policy question posed as if it were empirical. ✗ “Should Meridian close its five worst-performing stores?” “Should” mixes evidence with strategy, cost and values. REPAIR Extract the researchable core: what share of those stores' underperformance is explained by local factors that closure would not fix? PREDICTION WITHOUT MECHANISM A bare forecast with no explanatory content. ✗ “Will customer satisfaction improve next year?” Whatever happens, you learn nothing about why — so nothing transfers. REPAIR Anchor it in a mechanism: does delivery speed drive satisfaction, so that this year's logistics investment should raise next year's scores?

Discuss: diagnose and repair

  • Two questions, fresh from an imaginary Meridian board meeting — for each, name the flaw(s) and propose a repair:
    • “Why does our toxic workplace culture drive away young employees and annoy our customers?”
    • “Will things get better after the reorganisation?”
  • Aim your repairs at the four criteria: answerable, focused, feasible, non-trivial
  • Keep the goal in view too: is your repaired question exploratory, descriptive, or explanatory — and is that the right goal at this stage of Meridian’s project?

Hint: the first question manages to be leading, value-laden, and double-barrelled at once — flaws hunt in packs.

Conclusion

Conclusion

  • Research starts before data: the journey from a managerial problem to a researchable question is itself methodological work — and it is where most studies are won or lost
  • A good topic passes the tests of relevance, feasibility, and practicality — and sits at the right scope: not a field, not an incident
  • Every study serves a goal — exploration, description, or explanation — and the goal disciplines the question: what could be going on, what is happening, why is it happening
  • Sound questions are answerable, focused, feasible, and non-trivial; the common flaws — double-barrelled, leading, value-laden, unanswerable, too broad, trivial, unresearchable, mechanism-free prediction — are all failures of one of these
  • When we next meet, we take the step this session deliberately stopped short of: turning questions into hypotheses and variables, and choosing a research design
  • Questions and discussion are welcome

Exercise

Today’s exercise: From problem to question

QR code linking to the exercise worksheet

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Model answers: three questions, three goals

Model answers to Task 1: three questions, three goals Three model research questions, one per goal, linked by arrows marked feeds, because exploration feeds description and description feeds explanation. Exploratory: What do employees who have voluntarily left Meridian in the past twelve months say about their reasons for leaving? It builds the categories and hunches — pay, rotas, management, the unexpected — that later research will measure. Descriptive: How does voluntary staff turnover at Meridian vary across stores, roles, tenure bands, and the store/e-commerce divide? It maps what is happening, where and to whom, without yet claiming anything about causes. Explanatory: Does perceived workload under the new rota system affect front-line store employees' intention to quit? It relates a presumed cause to an effect: tells the board why people leave, and which lever to pull. These are one good set among several. The commonest error: an exploratory question that is really descriptive, such as how many Meridian employees are dissatisfied; it counts categories it already assumes, so it explores nothing. One good set among several: any questions grounded in the vignette that serve their goal and pass the four criteria EXPLORATORY What do employees who have voluntarily left Meridian in the past twelve months say about their reasons for leaving? What it produces builds the categories and hunches — pay, rotas, management, the unexpected — that later research will measure feeds DESCRIPTIVE How does voluntary staff turnover at Meridian vary across stores, roles, tenure bands, and the store/e-commerce divide? What it produces maps what is happening, where and to whom, without yet claiming anything about causes feeds EXPLANATORY Does perceived workload under the new rota system affect front-line store employees' intention to quit? What it produces relates a presumed cause to an effect: tells the board why people leave, and which lever to pull COMMONEST ERROR An “exploratory” question that is really descriptive: “How many Meridian employees are dissatisfied?” It counts categories it already assumes, so it explores nothing.

Model answers: diagnose and repair (1–4)

Model answers to Task 2: diagnose and repair, questions 1 to 4 Four cards, questions 1 to 4, each with the flaw, the criterion it violates, the original question and a model rewrite. Question 1: Double-barrelled, violating focused. Original: How satisfied are Meridian's employees with their pay and their opportunities for promotion? Model rewrite: Split it in two: How satisfied are Meridian's employees with their pay? How satisfied are they with their opportunities for promotion? Question 2: Leading (also value-laden), violating answerable. Original: Why does Meridian's outdated rota system force our best salespeople to resign? Model rewrite: Ask whether first: Is there an association between working under the new rota system and voluntary resignation among sales staff? Question 3: Value-laden (or: not researchable), violating answerable. Original: Is it fair that e-commerce staff can work from home while store staff cannot? Model rewrite: How do store and e-commerce employees differ in how fair they find Meridian's working arrangements, and how is that related to intention to quit? Question 4: Unanswerable, violating answerable. Original: Would Meridian's turnover have stayed at 14% if the company had never launched its e-commerce arm? Model rewrite: Have turnover rates risen more in the stores most affected by the e-commerce expansion than in the stores least affected? 1 DOUBLE-BARRELLED violates: focused “How satisfied are Meridian's employees with their pay and their opportunities for promotion?” MODEL REWRITE Split it in two: How satisfied are Meridian's employees with their pay? How satisfied are they with their opportunities for promotion? 2 LEADING · also value-laden violates: answerable “Why does Meridian's outdated rota system force our best salespeople to resign?” MODEL REWRITE Ask whether first: Is there an association between working under the new rota system and voluntary resignation among sales staff? 3 VALUE-LADEN · or: not researchable violates: answerable “Is it fair that e-commerce staff can work from home while store staff cannot?” MODEL REWRITE How do store and e-commerce employees differ in how fair they find Meridian's working arrangements, and how is that related to intention to quit? 4 UNANSWERABLE violates: answerable “Would Meridian's turnover have stayed at 14% if the company had never launched its e-commerce arm?” MODEL REWRITE Have turnover rates risen more in the stores most affected by the e-commerce expansion than in the stores least affected?

Model answers: diagnose and repair (5–8)

Model answers to Task 2: diagnose and repair, questions 5 to 8 Four cards, questions 5 to 8, each with the flaw, the criterion it violates, the original question and a model rewrite. Question 5: Too broad, violating focused, feasible. Original: What influences how people behave at work? Model rewrite: How does perceived workload relate to intention to quit among front-line store staff with under two years' tenure? Question 6: Trivial, violating non-trivial. Original: Do Meridian employees whose overtime goes unpaid feel less happy about their overtime than those who are paid for it? Model rewrite: How much does unpaid overtime contribute to intention to quit, relative to workload and relations with line managers? Question 7: Not researchable, violating answerable. Original: Should Meridian close its five worst-performing stores? Model rewrite: To what extent is the underperformance of the five worst stores explained by store-specific factors rather than company-wide ones? Question 8: Prediction without mechanism, violating non-trivial. Original: Will staff turnover at Meridian fall next year? Model rewrite: Does perceived workload drive resignations, such that the planned increase in store staffing should reduce turnover next year? 5 TOO BROAD violates: focused, feasible “What influences how people behave at work?” MODEL REWRITE How does perceived workload relate to intention to quit among front-line store staff with under two years' tenure? 6 TRIVIAL violates: non-trivial “Do Meridian employees whose overtime goes unpaid feel less happy about their overtime than those who are paid for it?” MODEL REWRITE How much does unpaid overtime contribute to intention to quit, relative to workload and relations with line managers? 7 NOT RESEARCHABLE violates: answerable “Should Meridian close its five worst-performing stores?” MODEL REWRITE To what extent is the underperformance of the five worst stores explained by store-specific factors rather than company-wide ones? 8 PREDICTION WITHOUT MECHANISM violates: non-trivial “Will staff turnover at Meridian fall next year?” MODEL REWRITE Does perceived workload drive resignations, such that the planned increase in store staffing should reduce turnover next year?

Model answers: plenary

Model answers to Task 3: the plenary questions Four panels. Two pairs, two different flaws: often both are right, because flaws hunt in packs; question 2 is both leading and value-laden, and any label the pair can defend earns credit. Did the repair change the goal: turning why the rota forces people to resign into whether the rota is associated with resigning is the right repair, not a retreat, because the pattern must be established before it is explained, in the sequence explore, describe, explain. Edit the wording or rebuild: wording flaws (1, double-barrelled; 2, leading) can be edited away; logic flaws (4, a counterfactual; 7, a decision question) must be rebuilt, and question 4 must be rebuilt around a comparison we can observe. What research can give the board: the evidence the decision needs, never the verdict itself; questions 3 and 7 mix evidence with values and strategy, so research supplies the empirical parts and the judgement stays with the board. Two pairs, two different flaws? 2 leading value-laden Often you are both right: flaws hunt in packs. Question 2 presupposes its answer and calls the rota “outdated”. Credit any label the pair can defend. Did the repair change the goal? “Why does the rota force … to resign?” “Is the rota associated with resigning?” The right repair, not a retreat: establish the pattern before explaining it. explore describe explain Edit the wording, or rebuild? Wording flaws: edit them 1 double-barrelled · 2 leading Logic flaws: rebuild them 4 counterfactual · 7 decision question No rewording makes a Meridian without e-commerce observable: rebuild 4 around a comparison we can see. What can research give the board? The evidence the decision needs — never the verdict itself Questions 3 (“is it fair?”) and 7 (“should we close?”) mix evidence with values and strategy. Research supplies the empirical parts; the judgement stays with the board.

Study guide

Full summary of this session, for revision: Research goals and research questions

QR code linking to the session handout

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