Format. Appendix F presents norms for beginning stem cues, ending stem cues, beginning fragment cues, and ending fragment cues. The target words are listed in alphabetical order in the first column, the next 10 columns provide information about the non-semantic cue or cues that generated it, and the next 10 columns present information about the target, such as its frequency of occurrence. The file is in text format with the columns of data separated by commas so it can be opened in StatView or Excel when column separation is desired. The file can also be opened in Word or BBEdit or in any software program that will open a text file. Finally, it is important to know that each of the targets presented in this file can be looked up in Appendix B whenever an investigator needs both a non-semantic and a semantic cue for the same target word. All of the target words appearing in this file are cross-referenced in the meaning files making it possible to manipulate type of cue or type of prime while holding normative cue-to-target strength as well as other word characteristics constant.
Data. Appendix F presents 2,883 words in the norms which were produced by at least one of several types of non-semantic cues. The cues producing these words consisted of beginning sounds, ending sounds, beginning fragment cues, or ending fragment cues. Examples of each type of cue for the word BEST are, respectively, BE read aloud, EST read aloud, and both BE_ _, and _ EST presented visually with spaces for missing letters indicated by the dashes. For some words, such as BEST, non-semantic cues were normed for each of the four types of cues whereas for others only 1-3 non-semantic cues were normed. The beginning sound norms were collected from two samples of subjects (n = 113 and n= 135). Each subject was given a booklet containing a list of blank lines and they were given to understand that we wanted them to write the first word they thought of when they heard each beginning sound. The sound was read to them over a tape recorder twice with a slight pause between repetitions, and they were asked to repeat it to themselves silently and then write the first word to come to mind that began with the same sound. Five seconds was allowed for writing each word and each person in each group was asked to respond to 90 beginning sounds, producing a total of 180 normed beginning sounds. These 180 sounds produced 1,296 of the target words appearing in the normative database. Of course, other words not appearing in the database were also produced but they are not represented here. The cues for targets produced by beginning sounds are not presented in Appendix F because such cues can be easily inferred from the target itself by pronouncing the initial letters up through the initial vowel sound, as in BE for BEST.
The ending sound norms were collected in the same manner. Given our greater interest in rhyme, these norms were actually collected first and in greater numbers. A total of 397 ending sounds were normed. In each of two samples (n = 184 and n = 201), 130 ending sounds that formed single rhymes (Woods, 1971) such as A, AB, ACH, and so on, were presented. A total of 123 of these sounds were unique to each group and 7 were repeated to provide a small sample for checking reliability which averaged r = .79 according to a Spearman Rank Correlation. In two other samples (n = 153 and n = 242), 144 double rhymes such as A' BE, AB' IT and A' BER were normed. It is important to note that the single and double rhyme sounds are separated in Appendix F by placing an asterisk next to the generated word for only the double sounds. Hence, if there is no asterisk present next to the target word listed, this should be taken to mean that the last few letters of this item beginning with the terminal vowel sound was used to form the sound cue, as with EST for BEST. The single and double rhyme sounds produced a total of 2,120 words from the database. Finally, the same female (CM) read the beginning and ending sounds in all groups.
The word fragment cues were collected by presenting participants with printed letters and spaces for missing letters as in BE _ _ and _ EST in booklets. Letter fragments were defined in terms of the letters that were present in the cue, e.g., a beginning letter fragment has at least its first letter present in the fragment. Participants were asked to produce the first word to come to mind that fit with the letters and spaces provided as the cue. For example, as suggested above, some people responded with the word BEST to each of these non-semantic cues. Five different samples were involved in collecting these norms and the number of participants differed considerably (n = 148, n = 132, n = 79, n = 67 and n = 59). Totals of 279 and 283 beginning and ending fragments cues, respectively, were normed and they produced 1,274 and 1,110 of the words appearing in the normative database. Because fragment cues vary substantially, they are presented in Appendix F.
In addition to presenting the words produced by one or more non-semantic cues, Appendix F provides the set size associated with each cue as well as the probability of its production in the subject sample. For example, the sound produced by pronouncing the beginning letters BE produced a total of 14 words sharing this sound, with this information appearing in the column labeled BSSQ--which stands for beginning set size of the cue. The probability of generating the word BEST from this sound provides an index of cue-to-target strength from the sound BE to the word BEST. A value of 0.04 in this case appears in the column labeled BSGQ--which, in shorthand terms, stands for beginning strength of the cue in relation to the target. In this shorthand the term beginning simply indicates that participants were told that the non-semantic cue they heard consisted of the beginning letters (as opposed to ending letters).
The ending sound EST had a set size of 20 different words (see ESSQ) and the probability of producing BEST from this sound was .38 (see ESGQ). Similarly, the fragment cues BE _ _ and _ EST produced this word with respective set sizes of 19 and 7 and with respective strengths of 0.06 and 0.42. Hence, the non-semantic norms provide information concerning the number of readily available words generally given to four types of non-semantic cues as well as estimates of baseline cue-to-target strength in the absence of recent experimenter controlled study. Quick Reference. Table 11 presents definitions for the abbreviations appearing on the columns in Appendix F: Abbreviations related to target characteristics are defined and described in Appendices A and B.
Table 11 | |
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Abbreviations of terms and their equivalencies in Appendix F. | |
Abbreviation | Equivalence |
TARGET | Response to Non-Semantic Cue |
BSSQ | Beginning: Set Size of Cue |
BSGQ | Beginning: Strength of the Cue |
ESSQ | Ending: Set Size of Cue |
ESGQ | Ending: Strength of the Cue |
BFQ | Beginning Fragment Cue |
BFSS | Beginning Fragment: Set Size |
BFSG | Beginning Fragment: Strength of the Cue |
EFQ | Ending Fragment Cue |
EFSS | Ending Fragment: Set Size |
EFSG | Ending Fragment: Strength of the Cue |
TSS | Target: Set Size |
TFR | Target: Frequency |
TCON | Target: Concreteness |
TH | Target is a homograph? |
TPS | Target: Part of Speech |
TMC | Target: Mean Connectivity Among its Associates |
TPR | Target: Probability of a Resonant Connection |
TRSG | Target: Resonant Strength |
TUC | Target: Use Code |
TUI | Target: Usability Index |