The Assumption Auction

Sale No. 001 · Twenty-five lots · Viewing open to all

The Assumption Auction

Confidence is the currency. Curiosity is the prize.

Every day we quietly buy assumptions without checking what’s inside: busy means productive, a polite yes means agreement, the best student becomes the best manager. Here they go under the gavel. You get 100 pretend tokens per lot to spread across your confidence. Then the lot is opened, and the only thing anyone takes home is a better question.

Take a paddle Browse the catalogue

No real money. No winners. No leaderboard. Tokens cannot be bought, won or exchanged; they exist only to make your confidence visible to you.

  • Sourced finding

    Backed by a specific reference in the drawer below. Please check it yourself; a link is a starting point, not a trophy.

  • Illustrative model

    An invented scenario or a piece of logic, used to show how something could work. Not data, and never presented as data.

  • Interpretation

    The auction house’s reasoned opinion. Thoughtful people disagree with some of these, and that’s welcome.

Every lot also carries a house reading: mostly holds, it depends or mostly doesn’t hold. It is an editorial judgment, not an answer key.

The saleroom

The auction floor

The live auction needs JavaScript, which seems to be switched off. Nothing is lost: every lot, its context, counterexamples and questions are in the catalogue below, readable as plain text.

The printed catalogue

Twenty-five lots, opened

Each card holds the full contents of a lot: what’s missing, a case that cuts the other way, a fairer reading and the questions worth asking before anyone bids. This catalogue works without JavaScript and without bidding.

Lot 01

Interpretation

“Busy means productive.”

Examine the lot
Missing context
Busyness describes inputs: hours, meetings, messages, motion. Productivity is about outputs, and whether they were worth the inputs. The two can travel together, but they are measured in different units.
A counterexample
A day of back-to-back calls and instant replies can end with nothing finished, while two quiet, uninterrupted hours produce the one thing that actually mattered.
A better reading
Busyness is easy to see, so it often stands in for results that are harder to see. Treat it as a clue about effort, not a verdict about output.

House reading: It depends

What would I need to ask first?

  • Productive at producing what, exactly?
  • Compared with which baseline: last month, a colleague, a quieter week?
  • Who decides what counts as an output here?

Lot 02

Illustrative model

“A polite yes means agreement.”

Examine the lot
Missing context
A “yes” can mean “I agree”, but it can also mean “I heard you”, “not in front of everyone”, or “I can’t really say no to you”. Which one depends on power, setting, custom and what refusing would cost.
A counterexample
A new team member says “Yes, sure” to a deadline in a group meeting while already doubting it can be met, because objecting in public feels riskier than slipping quietly later. (An illustrative scenario, not a reported case.)
A better reading
Agreement is easier to confirm in specifics than in tone: what will happen, by when, under which constraints, and what would make it slip.

House reading: It depends

What would I need to ask first?

  • What would it cost this person to say no here?
  • Did we agree on specifics, or only on a pleasant mood?
  • Is there a private, low-stakes way for them to raise a doubt?

Lot 03

Sourced finding

“The best student becomes the best manager.”

Examine the lot
Missing context
Doing a task brilliantly and helping other people do it well draw on overlapping but different skills. Grades and individual results mostly measure the first.
A counterexample
A top individual performer who prefers to fix everything personally may struggle once the job becomes coaching, delegating and making other people’s work easier.
A better reading
In a large study of sales workers across 214 firms, companies tended to promote their strongest sellers, yet higher pre-promotion sales were associated with weaker results among the people those new managers led; experience of working collaboratively was a better signal. It is one study in one field, about workers rather than students, so read it as a strong caution rather than a law.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What does the new role actually require, day to day?
  • What evidence do we have of those particular skills?
  • Is promotion the only way we know how to reward excellent work?

Check it: NBER: Promotions and the Peter Principle in the references drawer.

Lot 04

Sourced finding

“If lots of people choose it, it must be the best option.”

Examine the lot
Missing context
Popularity tells you how many people chose something. Their reasons can include quality, but also price, availability, advertising, habit, imitation and the path of least effort.
A counterexample
When an option is set as the default, many people simply stay with it. Decision-making research describes how switching retirement saving from opt-in to automatic enrolment (with an opt-out) substantially raised participation without changing the options themselves.
A better reading
Popularity is evidence that something is acceptable to many people under current conditions. Whether it is best for you depends on what you need and on how the choice was set up.

House reading: It depends

What would I need to ask first?

  • Best for whom, and at what?
  • How did most people come to choose it: actively, or by default?
  • What do the people who switched away say?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 05

Sourced finding

“People who do X are happier, so doing X makes people happier.”

Examine the lot
Missing context
When two things move together, the link could run in either direction, or a third factor could drive both. A correlation shows a pattern, not its cause.
A counterexample
If generous people report more happiness, generosity might lift mood, happier people might give more, or something like income might make both easier.
A better reading
Introductory research-methods material is clear that a correlation alone usually can’t tell you what causes what. Experiments that randomly assign people to conditions are the standard way to test a causal claim, though they aren’t always possible or ethical.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • Could the arrow point the other way?
  • What third factor could produce both?
  • Was anyone randomly assigned, or did people sort themselves?

Check it: Noba: Research Designs in the references drawer.

Lot 06

Sourced finding

“The more confident I feel, the more likely I am to be right.”

Examine the lot
Missing context
Confidence is a feeling about a judgment; accuracy is how well the judgment matches the world. They are related, but people are often more confident than their track record justifies.
A counterexample
In a classic classroom exercise, people give ranges they feel 98% sure will contain the true answers to general-knowledge questions. Most capture far fewer answers than that level of confidence implies.
A better reading
Confidence becomes more trustworthy once it has been checked against outcomes. Without that feedback, treat strong certainty as a reason to look for evidence, not a substitute for it.

House reading: It depends

What would I need to ask first?

  • How often have I felt this sure and been wrong?
  • What would I expect to see if I were mistaken?
  • Am I confident about the facts, or about being someone who knows?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 07

Sourced finding

“A positive result on an accurate test means it’s almost certainly true.”

Examine the lot
Missing context
Whether a positive result is probably right depends on three things together: how often the test catches true cases, how often it raises false alarms, and how common the condition was in the first place. That last one is the base rate.
A counterexample
If a condition is rare, even a fairly accurate test can produce more false alarms than true finds, simply because there are so many more people without the condition to be wrongly flagged. Try the base-rate model further down this page.
A better reading
Bayes’ theorem formalises how a prior probability (the base rate) combines with the strength of the evidence. Accuracy figures alone cannot answer the question; you also need to know how common the thing was before anyone tested.

House reading: It depends

What would I need to ask first?

  • How common is this among people like the one being tested?
  • What is the false-alarm rate, not just the hit rate?
  • Was there a specific reason to test, or was it routine screening?

Check it: SEP: Bayes’ Theorem in the references drawer.

Lot 08

Interpretation

“They haven’t replied, so they must be annoyed with me.”

Examine the lot
Missing context
“No reply yet” is an observation. “They’re annoyed” is one interpretation among many: busy, travelling, unwell, thinking it over, didn’t see it, assumed no reply was needed.
A counterexample
A message sits unread because it arrived in the middle of someone’s chaotic week and slid below newer notifications. Nothing about you entered the picture. (Illustrative.)
A better reading
Silence carries very little information on its own. If it matters, the cheapest evidence is usually a short, low-pressure follow-up.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What else would produce exactly this silence?
  • How long do they usually take to reply?
  • Is there a kind, easy way to simply ask?

Lot 09

Interpretation

“If the experts agree, the question is closed.”

Examine the lot
Missing context
Broad agreement among people who study a question carefully is strong evidence, often the best available. Its weight depends on whether they are experts in this question, how the agreement was established, and how settled the underlying evidence is.
A counterexample
A respected specialist offering a confident opinion well outside their field, or two quoted voices presented as “the experts”, carries far less weight than a field’s considered consensus.
A better reading
Consensus deserves heavy weight, not infinite weight. Settled for practical purposes is not the same as closed to new evidence. The useful skill is telling a real consensus from a borrowed one.

House reading: It depends

What would I need to ask first?

  • Experts in what, exactly?
  • How do we know they agree: a review, a joint statement, a headline?
  • What new evidence would they themselves accept as reopening it?

Lot 10

Sourced finding

“The first price you hear tells you what something is worth.”

Examine the lot
Missing context
An opening number tells you what someone is asking, which reflects their costs, hopes and tactics. On its own it says little about value.
A counterexample
Classroom demonstrations show estimates drifting towards whatever number is mentioned first, even an obviously arbitrary one, with people adjusting away from it too little. The pattern is called anchoring.
A better reading
Treat the first figure as information about the person who said it, not about the item. Form your own estimate from comparisons before you let anyone else’s number into the room.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What would I have guessed if I’d never heard that number?
  • What do comparable things actually sell for?
  • Who chose this starting point, and why?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 11

Illustrative model

“If it worked for me, it will work for you.”

Examine the lot
Missing context
One success shows that something can work under some conditions. It doesn’t show which conditions were essential, or how often it fails for others.
A counterexample
Picture a study routine that works for someone with a quiet room, flexible hours and nobody depending on them. The same routine may collapse for someone sharing a room and working evenings. (Illustrative.)
A better reading
Personal experience is real evidence about you. Before generalising it, look for the people it didn’t work for, and for what was different about them.

House reading: It depends

What would I need to ask first?

  • What was unusual about my situation?
  • Who tried this and found it didn’t work?
  • Which part was essential, and which part was luck?

Lot 12

Sourced finding

“The way a choice is described doesn’t change what I’d choose.”

Examine the lot
Missing context
The same outcome can be described as a gain (“200 of 600 are saved”) or as a loss (“400 of 600 are lost”). Logically nothing changes. Psychologically, quite a lot does.
A counterexample
In a well-known decision problem, most people pick the sure option when outcomes are framed as lives saved, and the gamble when exactly the same outcomes are framed as lives lost.
A better reading
Framing effects are a well-documented pattern in judgment research. A practical habit: restate any important choice the other way round and see whether your preference survives.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • How does this sound described the opposite way?
  • What reference point is being implied?
  • Who chose this framing, and why?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 13

Interpretation

“Hard work always pays off.”

Examine the lot
Missing context
Effort usually matters. Whether it pays off also depends on direction, feedback, timing, starting resources, other people’s decisions and plain luck.
A counterexample
Months of hard work on the wrong problem, or on a skill that stopped being valued, can produce little reward. Success stories rarely list the people who worked just as hard elsewhere.
A better reading
Effort is often necessary and rarely sufficient. A kinder and more accurate version: steady effort, pointed in a direction that gets regular feedback, improves your odds.

House reading: It depends

What would I need to ask first?

  • Pays off in what, and over what timescale?
  • What else was present in the success stories besides effort?
  • What feedback would tell me I’m working hard in the wrong direction?

Lot 14

Interpretation

“Older means wiser.”

Examine the lot
Missing context
Age brings more experience, and experience can build judgment, especially in stable areas with clear feedback. It can also carry outdated assumptions when the area has changed.
A counterexample
Someone with decades in a trade may read people superbly yet be working from old rules about a tool that changed last year; a younger colleague may know the tool and misread the room.
A better reading
Ask what the experience was in, and whether that world still works the way it did. Respect for experience and curiosity about change sit together comfortably.

House reading: It depends

What would I need to ask first?

  • Experience in what, specifically?
  • Has this area changed since that experience was gathered?
  • What would each generation notice that the other misses?

Lot 15

Interpretation

“Expensive means better quality.”

Examine the lot
Missing context
Price reflects materials and labour, but also brand, scarcity, positioning, distribution and what the seller believes buyers will pay.
A counterexample
A plain, inexpensive tool can outlast a premium one bought mostly for its name; equally, a cheap item can cost more over time if it has to be replaced twice.
A better reading
Price is a noisy signal of quality. Comparisons on the things you actually care about, ideally without seeing the label, tell you more than the tag.

House reading: It depends

What would I need to ask first?

  • What exactly am I paying for?
  • Is there a comparison that doesn’t show the brand?
  • Would I value this as much if it cost less?

Lot 16

Illustrative model

“The more detailed a story is, the more likely it is to be true.”

Examine the lot
Missing context
Details make a story vivid and easy to picture. But each added detail is one more condition that must hold, so a more specific story can never be more probable than the plainer version it contains.
A counterexample
“The shop closed early” is at least as likely as “the shop closed early because the owner went to a cousin’s wedding”, however much more convincing the second sounds.
A better reading
Vividness and probability pull in different directions. When a story feels compelling, separate the parts that have been checked from the parts that merely sound right.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • Which details are confirmed, and which are just vivid?
  • What is the simplest version that fits what we know?
  • Who would know if a particular detail were wrong?

Lot 17

Interpretation

“Someone who stays calm in a crisis doesn’t really care.”

Examine the lot
Missing context
Visible emotion and inner concern are only loosely connected. Temperament, training, custom, role and coping style all shape how feelings show.
A counterexample
A nurse speaking evenly during an emergency may care intensely; the calm is part of the job. Someone else may go quiet precisely because they are overwhelmed. (Illustrative.)
A better reading
Outward expression is a clue to read alongside context, not a gauge of how much someone cares. What people do over time usually says more.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What does this person’s calm help them do?
  • What have they done, not just shown?
  • How do they usually express worry?

Lot 18

Sourced finding

“When people choose their own group, comparing the groups can mislead you.”

Examine the lot
Missing context
If people choose which class, programme or habit they join, the groups may differ in many ways besides the thing being compared. That makes it hard to say what caused any difference in outcomes.
A counterexample
It isn’t always misleading: sometimes the self-chosen groups happen to be similar on everything that matters. The trouble is that you usually can’t tell that from the comparison alone.
A better reading
Research-methods texts draw exactly this line between experiments that randomly assign people and quasi-experiments that use existing groups: without random assignment, a confounding difference (say, more motivated students picking a demanding teacher) may explain the result. The open question is how large the distortion is in a given case.

House reading: Mostly holds

What would I need to ask first?

  • How did people end up in each group?
  • What else might differ between the groups?
  • Is there a comparison where assignment was closer to random?

Check it: Noba: Research Designs in the references drawer.

Lot 19

Sourced finding

“Once you know about a bias, you’re protected from it.”

Examine the lot
Missing context
Learning the name of a bias helps you recognise it in principle. Catching it in yourself, in the moment, under time pressure, is a different skill.
A counterexample
Plenty of people who can define anchoring are still pulled by an opening price. Knowing the trick doesn’t switch off the pull.
A better reading
Decision-making research summarised for students notes that early work found awareness alone did little to reduce bias. More helpful: slower, deliberate thinking for important choices, and changing the environment itself, for example with better defaults.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What process would catch this if I didn’t notice it?
  • Who could check my reasoning before I commit?
  • Can I change the setup instead of relying on vigilance?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 20

Sourced finding

“If I can easily think of examples, it must be common.”

Examine the lot
Missing context
How easily examples come to mind depends on how often something happens, but also on how vivid, recent, emotional or widely shared it was.
A counterexample
After a dramatic news story, a rare event can feel common simply because it is easy to picture, while a frequent but dull risk barely registers.
A better reading
Judging frequency by how readily examples surface is a useful shortcut that misleads in predictable ways; judgment research describes people leaning on information that is easy to retrieve. When it matters, look for a count.

House reading: It depends

What would I need to ask first?

  • Is this frequent, or just memorable?
  • Where would I find an actual count?
  • What common thing am I not hearing about?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 21

Sourced finding

“A larger, fairly gathered record usually tells you more than one vivid case.”

Examine the lot
Missing context
A single striking case is easy to remember and easy to over-weight. A larger record, gathered fairly, smooths out luck and shows the usual pattern.
A counterexample
“Fairly gathered” is doing real work. A large record of only the successes, or only the people who bothered to reply, can mislead more confidently than one honest anecdote.
A better reading
Accounts of decision-making often cite baseball professionals who over-weighted recent performance and what they saw with their own eyes, when multi-year records were the better guide. Big and fair beats small and vivid; big and biased is its own problem.

House reading: Mostly holds

What would I need to ask first?

  • How many cases does this rest on?
  • How were they chosen, and who is missing?
  • Does the vivid case look typical of the larger record?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 22

Sourced finding

“Looking back, it was obvious all along.”

Examine the lot
Missing context
After an outcome, the signals that pointed towards it become easy to see, while the signals that pointed elsewhere fade. The past starts to look more predictable than it was.
A counterexample
Before the result, the same signals that now look like warnings sat alongside others pointing the opposite way, and reasonable people disagreed.
A better reading
Hindsight bias, claiming to have known beforehand what we only learned afterwards, is a recognised pattern in judgment research. The simplest defence is to write predictions down before outcomes are known.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What did I actually predict, and where is it written?
  • Which signals pointed the other way at the time?
  • Would I have bet on this beforehand?

Check it: Noba: Judgment and Decision Making in the references drawer.

Lot 23

Illustrative model

“If nobody complains, everything is fine.”

Examine the lot
Missing context
A complaint requires that people notice a problem, believe someone will listen, and judge that speaking up is worth the cost. Remove any one of those and silence follows, problem or not.
A counterexample
Unhappy customers may simply stop coming back rather than complain; colleagues who expect complaints to be held against them may stay quiet.
A better reading
Silence is weak evidence of satisfaction. Signals that don’t depend on people volunteering, such as asking directly or noticing who leaves, tell you more.

House reading: It depends

What would I need to ask first?

  • How easy and safe is it to complain here?
  • Who has quietly left instead?
  • When did we last ask, rather than wait?

Lot 24

Interpretation

“If it’s free, it costs nothing.”

Examine the lot
Missing context
A price of zero can hide other costs: time, attention, personal data, future lock-in, or obligations that arrive later.
A counterexample
A free app may be funded by advertising shaped by what it learns about you; a free trial may be designed to make the full purchase feel like a small next step.
A better reading
“Free” describes the price at the counter, not the total cost. Asking how the provider sustains itself usually reveals what you are paying with.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • How does the provider keep the lights on?
  • What am I giving in time, attention or data?
  • What would leaving cost me later?

Lot 25

Sourced finding

“Changing your mind is a sign of weakness.”

Examine the lot
Missing context
Changing your mind because someone pressured you is one thing. Changing it because new evidence arrived is how learning is supposed to work.
A counterexample
A person who never revises any belief, whatever the evidence, isn’t demonstrating strength; they are simply not learning from anything new.
A better reading
Formal accounts of rational belief treat learning as updating: a prior degree of belief is revised in proportion to the strength of new evidence. Updating isn’t defeat; it is the mechanism of becoming less wrong.

House reading: Mostly doesn’t hold

What would I need to ask first?

  • What new evidence actually arrived?
  • Am I moving because of evidence, or because of pressure or fatigue?
  • How far should this evidence move me: a little, or all the way?

Check it: SEP: Bayes’ Theorem in the references drawer.

The auctioneer’s notebook

Ten better questions

A question can close a conversation or open a lot. These upgrades aren’t clever tricks; they simply ask for the information an assumption skipped.

  1. Instead of “Is this true?”

    Try “Under what conditions would this be true, and when would it fail?”

    Swaps a verdict for a map of the territory.

  2. Instead of “Do you agree?”

    Try “Which part of this would you change if you could?”

    Gives a polite person a safe place to put their doubt.

  3. Instead of “Does it work?”

    Try “Compared with what, for whom, measured how?”

    Every claim of success hides a comparison; this one asks to see it.

  4. Instead of “Why would anyone do that?”

    Try “What situation would make that a sensible choice?”

    Assumes good reasons until shown otherwise, and often finds them.

  5. Instead of “Is this study any good?”

    Try “Who was studied, how were they grouped, and what was measured?”

    Turns a vibe check into three checkable facts.

  6. Instead of “Are you sure?”

    Try “What would you expect to see if you were wrong?”

    Invites a test rather than a defence.

  7. Instead of “Is this common?”

    Try “Out of how many? What’s the usual rate?”

    Puts the base rate on the table before the story arrives.

  8. Instead of “Who’s right here?”

    Try “What evidence would each of us accept as settling it?”

    Moves a disagreement from people to evidence.

  9. Instead of “Can you get it done by Friday?”

    Try “What would need to be true for Friday to work, and what would you drop?”

    Makes room for an honest answer instead of a polite yes.

  10. Instead of “Is this person an expert?”

    Try “Is this question inside their field, and do others in that field agree?”

    Separates real authority from borrowed authority.

Before you bid

Uncertainty and base rates

Uncertainty is not a failure of nerve. It is an honest description of how much you know. That’s why this auction asks you to spread tokens rather than pick a side: 60 on one paddle and 40 on another is a perfectly respectable bid.

Three working ideas

  1. Confidence comes in degrees. “Probably”, “maybe” and “almost certainly” are different claims. Saying which one you mean is more useful than sounding sure.
  2. Start with how common something is. The base rate is how often a thing happens in the relevant group before any specific evidence arrives. Judgment research describes people routinely under-weighting it when a vivid detail is present.
  3. Update in proportion. In formal accounts of reasoning under uncertainty, new evidence moves a belief by an amount that depends on how much more likely that evidence is if the belief is true than if it is false. Strong evidence moves you a lot; weak evidence, a little.

Illustrative model The panel opposite uses invented numbers for an imaginary trait in an imaginary town of 1,000 people. It shows the arithmetic, not any real test.

An imaginary town of 1,000

Suppose 5% of the town has a trait (50 people). A check correctly flags 80% of them (40 people) but also wrongly flags 10% of everyone else (95 of 950 people). That makes 135 flags, of which only 40, about 30%, are correct. A fairly accurate check, applied to something uncommon, produces mostly false alarms.

Conditions of sale

House rules

Nobody is scored against anybody

There are no accounts, no leaderboard and no comparison with other visitors. The Auction room shows a private ledger of your own bids so you can notice your habits. The Reading salon switches off every number and tally. Neither room ever sees anyone else.

The tokens are pretend

They can’t be bought, earned, won or cashed in, and nothing is staked. The auction is a way to make confidence visible, not a game of chance.

Your words stay with you

Anything you type is processed in your browser. There is no server, no analytics, no cookies and no third-party code. Saving to this device is opt-in, and you can download or delete everything from the ledger at any time.

The house can be wrong

House readings are judgments, sourced lots are only as good as their sources, and illustrative scenarios are invented. If you think a lot is mislabelled, that’s the auction working as intended.

The references drawer

Four checked sources, each tied to the specific claims it supports. Links open the original publishers. Everything not listed here is labelled on its lot as an illustrative model or an interpretation.

  1. Bazerman, M. H. “Judgment and Decision Making.” Noba Textbook Series: Psychology.

    Supports lots 04, 06, 10, 12, 19, 20, 21 and 22, and the note on base rates: the overconfidence range exercise, anchoring, gain/loss framing, the power of defaults, the finding that awareness alone did little to reduce bias, and descriptions of availability, hindsight and insensitivity to base rates and sample sizes.

  2. Scollon, C. N. “Research Designs.” Noba Textbook Series: Psychology.

    Supports lots 05 and 18: why correlation alone rarely establishes cause, third variables, random assignment, and confounds in quasi-experiments that use existing groups.

  3. Joyce, J. “Bayes’ Theorem.” Stanford Encyclopedia of Philosophy.

    Supports lot 07, lot 25 and the uncertainty section: combining base rates with a test’s true- and false-positive rates, likelihood ratios, and learning modelled as revising a prior belief in light of evidence.

  4. Benson, A., Li, D. & Shue, K. “Promotions and the Peter Principle.” NBER Working Paper 24343 (2018); published in the Quarterly Journal of Economics (2019).

    Supports lot 03: in sales data from 214 firms, top sellers were more likely to be promoted, stronger pre-promotion sales were associated with weaker subordinate performance, and collaboration experience predicted better managerial results.

Further reading for evidence literacy: the Noba Project (free introductory psychology modules) and the Stanford Encyclopedia of Philosophy. Starting points, not proof by themselves.