Part of Test 3 (My Study Guide) Flashcards
Language: What is it?
- No easy definition is likely to distinguish complex communication systems from “true language” to all researchers’ satisfaction
- A shared system of symbols and rules that allows us to communicate
Language Universals
-A simple definition is difficult, but we can identify features that are universal to human language
- Features:
- Semanticity
- Arbitrary
- Flexibility
- Naming
- Displacement
- Productivity/Generativity
Semanticity
- Language conveys a meaning
- Ex: coughing alone doesn’t express your flu as well as you saying, “I have the flu.”
Arbitrary
- There’s no inherent connection between the symbols and their referents (words and meaning)
- Ex: of “yes” - the word “yes” doesn’t say anything about what it means; the way it looks doesn’t say anything about what it means
Flexibility
- Since connections between words and referents are arbitrary, we can change them
- Ex: Slang changed the meaning of some words in particular contexts (bad, sick, wicked, minute, truthiness)
- Ex: Shakespeare made up a lot of words
Naming
- We name everything…if it doesn’t have a name, we make one up
- Ex: In an unfamiliar environment: “The blue thingy…” “That little doohickey there…”
Displacement
- We communicate about things that are not present and may or may not happen. We project into the future and the past.
- Ex: Well, if I have to work tonight, then tomorrow night I can do homework, and then if I get all that done I can go on a road trip this weekend. Unless they don’t feel like it; then maybe we can…
Productivity/Generativity
- We produce/generate novel ways of saying things rather than repeating the same sequences over and over
- Ex: “Oh, my God. There’s a snake! There’s a snake over there!” “A snake it on the ground.”
Levels of Language - Grammar
-The complete set of rules that will generate acceptable utterances, but not illegal utterances
- Thought to operate on several levels:
- Phonology
- Lexical
- Syntax
- Conceptual
- Belief
- Read about 4 and 5 in book!
- Belief
Phonology and Phonemes
-Phonology: a language’s sounds and rules for combining sounds
- Phonemes: smallest segment of sound in a given language
- Ex: /a/ - “table”; /ae/ - “sat”; /b/ - “ball”; /k/ - “snake”’ /d/ - “door”; /E/ - “me”
- Phoneme boundaries: boundaries by which we identify phonemes
- Ex: English: Princess and pituitary: “p” sounds the same, even though there are physical differences
- Ex: Spanish: No difference between “s” and “z” – Ice and eyes sound the same for native spanish speakers
Levels of Language - Lexical Level
-Lexical level: words and their meanings
- Morphemes: smallest linguistic unit that has semantic meaning to it; if can’t break down into smaller units
- Ex: stop
- Ex: Unstoppable: 3 morphemes
- Un – 2 phonemes /u/, /n/– NOT
- Stop – 4 phonemes /s/,/t/,/o/, /p/– HALT
- Able – 3 phonemes: /ae/, /b/, /l/– ABILITY
- Polysemy: multiple meanings (activating semantic network and deactivating the irrelevant stuff)
- We resolve the meaning through context:
- Step 1: Activate all meanings at a low level
- Step 2: Deactivate irrelevant meanings based on context
-Ex: “She drove into the bank.”
Levels of Language - Syntax
-Syntax: the structure of a sentence; how to put words in a sequence so they’re meaningful
- Planning how to say something
- -Given new strategy: we construct sentences based in part on the accessibility of the meaning; gonna say easy stuff first because more accessible in semantic network
- Why? We start speaking once the 1st part has been planned but before the end has been planned
- More complex syntactical structures require more planning
-Ex: “I want a donut.” vs. “It would be pleasant, if not downright enjoyable, to eat a donut in the not so distant future, and I will take advantage of the opportunity to do so should it arise.”
Comprehension
-Additional processes that are involved in understanding real-world samples of language and text
- Comprehension as a structure-building framework
- Like building a house out of legos
-1. Lay the foundation form the initial representations, capture meaning
- Mapping additional concept meanings and inferences get added; starting to make inferences
- Ex: She was glad that snow made people….?
- Mapping additional concept meanings and inferences get added; starting to make inferences
- Shifting to a new structure encounter change cues that require new structures
- Ex: the check that she’d get from….?
- Shifting to a new structure encounter change cues that require new structures
- She drove into the bank to get some money.
- She was glad that the snow made people stay at home, so there wasn’t much traffic.
- The check she’d get from the insurance company for the accident would help her pay off her credit card bill.
Comprehension - Mental Structure
-A mental representation of the situation conveyed by language; mental representation of what you’re reading
Comprehension - Situation Models
-A mental simulation of the world described by a text – includes prior semantic and episodic knowledge
- Ex:
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- The door swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- ‘The firs’-years, Professor McGonagall,’ said Hagrid.
- ‘Thank you, Hagrid. I will take them from here.’
- Bridging inference: make a connection between concepts that may or may not be explicitly stated
- Ex:
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- THE DOOR swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- [IT] swung open at once. A tall, black-haired witch in emerald-green robes stood there. She had a very stern face and Harry’s first thought was that this was not someone to cross.
- Hagrid raised a gigantic fist and knocked three times on the castle door.
- Authorized vs. Unauthorized inferences
- Authorized: Inference that speaker/author intends for you to make
- Unauthorized: Inference that speaker/author did NOT intend for you to make
- Ex of authorized: Hagrid raised a gigantic fist and knocked three times on the castle door. The door swung open at once. A tall, black-haired witch in emerald-green robes stood there. SHE had a very stern face and Harry’s first thought was that this was not someone to cross.
- Ex of unauthorized: “You look nice today.” “So I looked bad yesterday?”
Comprehension (Wrapped Up)
- Mental structures → mental representations, structure building (basic building blocks)
- Situation models → simulations, using mental structures, drawing on prior knowledge, allows you to make inferences
Language and the Brain
- Includes:
- Broca’s Area: Involved in speech planning and programming
- Arcuate Fasciculus: Axons that connect Broca’s and Wernicke’s areas – communication between the regions
- Wernicke’s Area: Involved in language understanding; come up with meaning
- Aphasia: language impairment; type depends on…?
Types of Aphasia
- Broca’s Aphasia
- Wernicke’s Aphasia
Broca’s Aphasia
- Brain Area Affected: lateral frontal lobe
- Spontaneous Speech: Nonfluent
- Comprehension (if what they’re saying makes sense or not): Good
- Repetition: Poor
- Naming: Poor
- May be able to read, but writing often difficult
- Usually aware of the problem
Wernicke’s Aphasia
- Brain Area Affected: lateral temporal lobe
- Spontaneous Speech: Fluent
- Comprehension: Poor
- Repetition: Poor
- Naming: Poor
- Reading and writing usually impaired
- Usually unaware of the problem
How we make decisions?
- Heuristics (ex: when playing blackjack: greater than 15? No more cards)
- Algorithms
Heuristic
- A rule of thumb; a shortcut
- More automatic
- Ex: Playing blackjack
Algorithm
- A rule or procedure that will provide a correct answer
- More controlled
Common Heuristics
- Frequency/Probability Judgements
- The availability heuristic
- The representative heuristic
- Gambler’s fallacy
- Base rate neglect
- Sample size (law of large numbers)
- Blame Judgements
- Counterfactual thinking
Frequency Judgment
-A judgement about which of a set of choices happens most often
Availability Heuristic
-We make a decision based on the ease with which the relevant information comes to mind (how quickly it comes to mind)
- Ex:
- Are there more words that start with “r” or more words with “r” in the 3rd position?
- Are there more deaths from tornadoes or asthma?
- The government has $1 billion to put toward one project. Should it be put toward more protection from terrorism or better infrastructure (e.g., roads and bridges)?
- Remember X times you were assertive. How assertive are you?
Representative Heuristic
-Judging the probability of something based on how much it resembles its population or the process that produced it
- Ex: For the next 6 babies born in the US, which of the following sequences is most likely?
- BBBBBB(doesn’t represent population) GGGBBB (too orderly) GBBGBG (random and does represent well!)
- All are equally likely
The Gambler’s Fallacy
- The FALSE belief that random processes (coin flips, roulette wheels, etc.) are sensitive to prior outcomes
- Ex: You watch a fair coin come up heads 5 times in a row. If you bet $10 on the next coin toss, do you bet heads or tails?
Base Rate Neglect
-Failure to take the baseline probabilities of events into consideration
- Ex: Steve is shy and withdrawn, usually helpful, but with little interest in people. Meek and tidy, he loves order and structure and has a passion for detail. Is Steve a librarian or a farmer?
- US Demographics: about 3.2 million farmers, and about 178,000 librarians, so farmer more likely, but people think librarian
Insensitivity to Sample Size
-Belief that small and large samples should be equally representative of the parent population
- Ex: At one hospital, about 20 babies are born each day. At another hospital, about 50 babies are born each day. For one year, the hospitals recorded the number of days when 60% or more of the babies born were female. Which hospital do you think had more days like that?
- Small hospital has more days like this
The Law of Large Numbers
- The larger the sample size, the more representative the sample will be!
- At one hospital, about 20 babies are born each day. At another hospital, about 50 babies are born each day. For one year, the hospitals recorded the number of days when 60% or more of the babies born were female. Which hospital do you think had more days like that?