ࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢ⟬ฟࣝࢦࣜࢬ࣒ࡢẚ㍑ ྛࣝࣇ࣋ࢵࢺࡢ୍⯡ⓗዲពᗘಶேࡢᛂഴྥ╔┠ࡋࡓศᯒ ὠ⏣ ᜤ ឡ▱ᏛἨᏛ A comparison of the algorithms for calculating the name letter effect Hisamitsu Tsuda ࣮࣮࢟࣡ࢻ㸸ࢿ࣮࣒ࣞࢱ࣮ࢸࢫࢺ name letter testࠊࢽࢩࣕࣝ㑅ዲㄢ㢟 initial preference taskࠊ ⮬ᑛᚰ self-esteemࠊㄆ▱ࣂࢫ cognitive bias 1㸬ၥ㢟 ᚰࡑࡢࡶࡢࢆࡼࡾṇ☜ࡽ࠼ࡿࡓࡵࡢ◊✲ࡶ ✚ࡳ㔜ࡡࡽࢀ࡚࠸ࡿࠋࡇࢀࡲ࡛ࠊ₯ᅾⓗ⮬ᑛ ⮬ᕫㄆ▱㛵ࡍࡿࡇࢀࡲ࡛ࡢ◊✲࡛ࠊேࡣ୍ ᚰࢆ ᐃࡍࡿࡓࡵࡢᡭἲࡀᩘከࡃ⪃ࡉࢀ࡚ࡁ ⯡ⓗ⮬ᕫᑐࡋ࡚࣏ࢪࢸࣈ࡞ែᗘࢆ᭷ࡋ࡚ ࡓࡀࠊ᭱ࡶᗈࡃ⏝࠸ࡽࢀ࡚࠸ࡿࡶࡢࡢࡦࡘࡀ ࠾ࡾࠊ⌧ᐇ௨ୖ⮬ᕫࢆ࣏ࢪࢸࣈࡽ࠼ࡓ ࢿ࣮࣒ࣞࢱ࣮ࢸࢫࢺ(name letter test)࡛࠶ࡿࠋ ࡾ(e.g., Alicke & Olesya, 2005)ࠊ⮬ศ㒔ྜࡼ ࡇࢀࡣࠊྛࣝࣇ࣋ࢵࢺᑐࡍࡿዲពᗘ㸦࠶ ࡃ≀ࢆゎ㔘ࡋࡀࡕ࡛࠶ࡿ(e.g., Miller & Ross, ࡿ࠸ࡣ㨩ຊᗘ㸧ࢆ┤ឤⓗホᐃࡋ࡚ࡶࡽ࠺࠸ 1975)ࡇࡀࡉࡲࡊࡲ࡞ᐇ㦂ࡸㄪᰝࢆ㏻ࡌ࡚᫂ ࠺༢⣧࡞ㄢ㢟࡛ࠊ⮬ศࡢྡ๓ྵࡲࢀ࡚࠸ࡿ ࡽࡉࢀ࡚ࡁࡓࠋࡇࢀࡽࡣ୍✀ࡢㄆ▱ࣂ ࣝࣇ࣋ࢵࢺࡢ┦ᑐⓗ࡞ዲពᗘࢆ₯ᅾⓗ⮬ᑛᚰ ࢫ࡛࠶ࡿࡀࠊࣂࢫ࠸ࡗ࡚ࡶᚲせ࡛ྲྀࡾ ࡢᣦᶆࡍࡿࠋෑ㢌♧ࡋࡓ࠸ࡃࡘࡢ◊✲ 㝖࡞ࡅࢀࡤ࡞ࡽ࡞࠸ᛶ㉁ࡢࡶࡢ࡛ࡣ࡞ࡃࠊࡴ ྠࡌࡃࠊࡇࡢㄢ㢟࡛ࡶ⮬ᕫᑐࡍࡿ࣏ࢪࢸࣈ ࡋࢁ⢭⚄ⓗᗣࡢ⥔ᣢ㔜せ࡞ᐤࢆࡋ࡚࠸ࡿ ࡞ែᗘࡀほᐹࡉࢀ࡚࠾ࡾࠊ୍⯡ⓗࠊ⮬ศࡢྡ ࡇࡶᣦࡉࢀ࡚࠸ࡿ(Taylor & Brown, 1988; ๓ྵࡲࢀ࡚࠸ࡿࣝࣇ࣋ࢵࢺࡣࡢࣝࣇ 1994)ࠋࡇ࠺ࡋࡓ࣏ࢪࢸࣈ࡞ࡺࡀࡳࡣࠊ㢧ᅾ ࣋ࢵࢺࡼࡾࡶዲࡲࢀࡓࡾࠊ⮬ศࡢྡ๓ྵࡲ ᣦᶆࡢࡳ࡞ࡽࡎ₯ᅾᣦᶆࢆ⏝࠸ࡓ◊✲࡛ࡶ☜ㄆ ࢀࡿࣝࣇ࣋ࢵࢺᑐࡍࡿዲពᗘࡣࡑࡢࣝ ࡉࢀ࡚࠾ࡾࠊ୍⯡ⓗ₯ᅾⓗ⮬ᑛᚰࡣ࣏ࢪࢸ ࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ⓗ࡞ዲពᗘࡼࡾࡶ㧗࠸ ࣈ೫ࡗ࡚࠸ࡿࡇࡀ᫂ࡽࡉࢀ࡚࠸ࡿ ഴྥࡀ࠶ࡿࠋࡇࢀࢆࢿ࣮࣒ࣞࢱ࣮ຠᯝࡪ (Farnham et al., 1999)ࠋࡇࡢᩥ⬦ࡢ◊✲࡛⯆ (Nuttin, 1985; 1987)ࠋ₯ᅾⓗ⮬ᑛᚰࡣࠊࠕ⮬ᕫ ῝࠸ࡢࡣࠊ㢧ᅾᣦᶆ࡛ࡣ᪥ᮏேࡢ⮬ᑛᚰᚓⅬ ⤖ࡧࡘ࠸ࡓᑐ㇟ࡸ⮬ᕫ㞳ࡋࡓᑐ㇟ཬࡰ ࡣ⡿ேࡼࡾࡶప࠸ࡢࡶࢃࡽࡎ(Heine ࡍࠊෆほ࡛ࡣ≉ᐃࡉࢀ࡞࠸㸦࠶ࡿ࠸ࡣṇ☜ et al.,1999)ࠊ₯ᅾᣦᶆ࡛ࡣᙼࡽྠ➼ࡢᚓⅬ ≉ᐃࡉࢀࡓ㸧⮬ᕫែᗘࡢຠᯝࠖᐃ⩏ࡉࢀࡿ ࢆ♧ࡍ(Yamaguchi et al., 2007)Ⅼ࡛࠶ࡿࠋࡇ (Greenwald & Banaji,1995)ࠋࡋࡓࡀࡗ࡚ࠊࢿ ࡢࡇࡽࠊ᪥ᮏேࡢ⮬ᑛᚰࡣᐇ㝿ࡣḢ⡿ே ࣮࣒ࣞࢱ࣮ຠᯝࡀࡁ࠸₯ᅾⓗ⮬ᑛᚰࡀ㧗 ẚ࡚ࡶపࡃ࡞࠸ࡀࠊㅬ㐯ࠊ⪅㓄៖ࠊ㞟ᅋ ࠸ࡇ࡞ࡿࠋ ⩏ഴྥ࡞ࡢᙳ㡪ࢆཷࡅ࡚⾲㠃ⓗࡣపࡃࡳ ࢿ࣮࣒ࣞࢱ࣮ຠᯝࡣ≉ࢽࢩࣕࣝ࠾࠸࡚ ࠼࡚࠸ࡿ࡞ࡢྍ⬟ᛶࡀ⪃࠼ࡽࢀࠊࡑࡢヲ⣽ࢆ 㢧ⴭ࡛࠶ࡿࡇࡀࢃࡗ࡚࠸ࡿ(Kitayama & ᫂ࡽࡍࡿࡓࡵࡢ◊✲ࡀ┒ࢇ⾜ࢃࢀ࡚࠸ Karasawa, 1997)ࠋࡑࡢࡓࡵࠊ᭱㏆ࡢ◊✲࡛ࡣ ࡿࠋ ࢽࢩࣕࣝࡢࡳࢆศᯒᑐ㇟ࡍࡿࡇࡀከ࠸ ࡇ࠺ࡋࡓ◊✲ࡀ⾜ࢃࢀࡿ୍᪉࡛ࠊ₯ᅾⓗ⮬ᑛ (e.g., Stieger et al., 2012)ࠋࡇࡢሙྜࠊㄢ㢟⮬ － 65 － 愛知学泉大学・短期大学紀要 యࡣࢿ࣮࣒ࣞࢱ࣮ࢸࢫࢺࡲࡗࡓࡃྠࡌ࡛࠶ࡿ ࠾ࠊྛࣝࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ⓗ࡞ዲពᗘ ࡀࠊࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢศᯒᑐ㇟ࡀࢽࢩࣕࣝ ಶேࡢᛂഴྥࡢᙳ㡪ࢆྠ⤫ไࡍࡿࣝ ࡢࡳ࡛࠶ࡿࡇࢆ᫂☜♧ࡍࡓࡵࢽࢩࣕࣝ ࢦࣜࢬ࣒ࡣࡶ 2 ࡘ࠶ࡾ㸦Double-correction 㑅ዲㄢ㢟(initial preference task)ࡶࡪࠋࢿ algorithm: ࣮࣒ࣞࢱ࣮ຠᯝ࠸࠺⏝ㄒࡣࠊ⮬㌟ࡢྡ๓ྵ double-correction algorithm : Z-algorithm㸧 ࠊ ࡲࢀࡿࡍ࡚ࡢࣝࣇ࣋ࢵࢺᑐࡍࡿ㑅ዲຠ ࡇࢀࡽࡶྠᵝ᳨ウࡉࢀ࡚࠸ࡿࡀࠊI-algorithm ᯝࢆᣦࡍሙྜࡶ࠶ࡿࡋࠊࢽࢩࣕࣝࡢࡳࡢ㑅 ࡢࡳ࡞ࡽࡎ B-algorithm ࡸ S-algorithm ẚ ዲຠᯝࢆᣦࡍሙྜࡶ࠶ࡿࡀࠊ᭱㏆ࡢࢇࡢ ࡚ࡶ≉ඃࢀ࡚࠸ࡿࡣ࠸࠼࡞࠸⤖ᯝ࡞ࡗ ◊✲࡛ࡣᚋ⪅ࡢព࡛⏝࠸ࡽࢀ࡚࠸ࡿࠋᮏ◊✲ ࡚࠸ࡿࠋ D-algorithm; Z-transformed LeBel & Gawronski(2009)࡛ࡣ I-algorithm ࡶྠᵝ࡛࠶ࡿࠋ ࢽࢩࣕࣝ㑅ዲㄢ㢟ࡣࠊᏳᐃ࡞₯ᅾᣦᶆࡶ ࡀ᭱ࡶ᥎ዡࡉࢀ࡚࠸ࡿࡀࠊࡇࡢࣝࢦࣜࢬ࣒࡛ ከ࠸୰࡛ẚ㍑ⓗ㧗࠸ಙ㢗ᛶࡀ☜ㄆࡉࢀ࡚࠸ࡿ ࡶ࡞࠾ᚓⅬࡢゎ㔘ࡣὀពࢆせࡍࡿሙྜࡀ࠶ࡿࠋ (Bosson et al., 2000)ࠋࡑࡢࡓࡵࠊࢽࢩࣕࣝ ࠼ࡤࠊࡁ࡞ࢹ࣮ࢱࡢ೫ࡾࡀᏑᅾࡍࡿሙྜ 㑅ዲㄢ㢟ࡣ₯ᅾⓗ⮬ᑛᚰࡢ ᐃἲࡋ࡚⡆౽࡛ ࡣ⿵ṇࡀᶵ⬟ࡋ࡞࠸ྍ⬟ᛶࡀ࠶ࡿࠋᴟ➃࡞ලయ ಙ㢗ᛶࡶ㧗࠸ᡭἲ࡛࠶ࡿ࠸࠼ࡿࡀࠊࢿ࣮࣒ࣞ ࡋ࡚ࡣࠊ7 ௳ἲ࡛ᅇ⟅ࢆồࡵࡓࡁ≉ᐃ ࢱ࣮ຠᯝࡢ⟬ฟ࠶ࡓࡗ࡚ࡣᕤኵࡀᚲせ࡛࠶ࡿࠋ ࡢࣝࣇ࣋ࢵࢺᑐࡍࡿዲពᗘᖹᆒࡀ 7 ࡛࠶ ࠼ࡤࠊࢽࢩࣕࣝᑐࡍࡿዲពᗘࡽࠊࡑࡢ ࡗࡓሙྜࠊB-algorithm ࡸ I-algorithm ࢆ⏝࠸ ࢽࢩࣕࣝࢆྵࡲ࡞࠸ேࡓࡕࡢࡑࡢࣝࣇ࣋ ࡿࠊࡑࡢࣝࣇ࣋ࢵࢺࢆࢽࢩࣕࣝࡶࡘ ࢵࢺᑐࡍࡿዲពᗘࡢᖹᆒ್ࢆᘬࡃ᪉ἲࡀ࠶ࡿ ಶேࡢࢿ࣮࣒ࣞࢱ࣮ຠᯝࡣࠊཎ⌮ⓗࢮࣟࡼࡾ (LeBel & Gawronski(2009)࡞ࡽࡗ࡚ࠊᮏ◊ ࡁࡃ࡞ࡾ࠼࡞࠸ࠋࡘࡲࡾࠊ࣏ࢪࢸࣈ࡞₯ᅾ ✲࡛ࡣࡇࢀࢆ Baseline-corrected algorithm: ⓗ⮬ᑛᚰࢆࡶ࡚࡞࠸ࡇ࡞ࡗ࡚ࡋࡲ࠺ࠋᐇ㝿 B-algorithm ࡪ)ࠋࡇࡢ᪉ἲࡣࡋࡤࡋࡤ⏝ ࡣዲពᗘᖹᆒࡀ᭱࡞ࡿࡇࡣ࠶ࡾ࠼࡞࠸ ࠸ࡽࢀࡿࡀࠊྛࣝࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ⓗ ࡀࠊࡇࢀ㏆࠸⌧㇟ࡀ⏕ࡌࡿྍ⬟ᛶࡣṧࡉࢀ࡚ ࡞ዲពᗘࡢࡳࢆ⪃៖ࡋ࡚࠾ࡾࠊಶேࡢᛂഴྥ ࠸ࡿࠋࡲࡓࠊS-algorithm ࡛ࡣࣝࣇ࣋ࢵࢺ ࢆ⤫ไࡋ࡚࠸࡞࠸࠸࠺ḞⅬࢆࡶࡘࠋࡇࢀᑐ ࡢ୍⯡ⓗዲពᗘࢆィ⟬⏝࠸࡞࠸ࡓࡵࠊㄡࡶࡀ ࡋ࡚ࠊಶேࡢࢽࢩࣕࣝᑐࡍࡿዲពᗘࡽ ዲࡴࡼ࠺࡞ࣝࣇ࣋ࢵࢺࢆࡓࡲࡓࡲࢽࢩࣕ ࢽࢩࣕࣝ௨እࡢዲពᗘࡢᖹᆒ್ࢆᘬ࠸ࡓ್ࢆồ ࣝࡶࡗ࡚࠸ࡿࡔࡅ࡛ࡶ㧗࠸ࢿ࣮࣒ࣞࢱ࣮ຠᯝ ࡵࡿ᪉ἲࡶ࠶ࡿ(LeBel & Gawronski(2009) ࡀ⟬ฟࡉࢀ࡚ࡋࡲ࠺ࡇ࡞ࡿࠋ࠼ࡤࠊࣝ ࡞ࡽࡗ࡚ࠊᮏ◊✲࡛ࡣࡇࢀࢆ Self-corrected ࣇ࣋ࢵࢺࡢ A ࡣ᪥ᮏ࠾࠸࡚ࡣ㧗࠸ホ౯ࢆព algorithm: S-algorithm ࡪ)ࠋࡇࡢ᪉ἲࡣࠊ ࡍࡿࡓࡵࠊ୍⯡ⓗዲࡲࢀࡸࡍ࠸ࣝࣇ࣋ ࡉࡁࡣᑐࠊྛࣝࣇ࣋ࢵࢺᑐࡍ ࢵࢺ࡛࠶ࡿᛮࢃࢀࡿࡀࠊࡑࡢሙྜࠊ ࡿ୍⯡ⓗ࡞ዲពᗘࡢᙳ㡪ࢆ⪃៖ࡋ࡚࠸࡞࠸ࠋࡋ S-algorithm ࢆ⏝࠸ࡿࠊA ࢆࢽࢩࣕࣝࡶ ࡓࡀࡗ࡚ࠊࢿ࣮࣒ࣞࢱ࣮ຠᯝࢆ⟬ฟࡍࡿ㝿ࡣࠊ ࡗ࡚࠸ࡿಶேࡢࢿ࣮࣒ࣞࢱ࣮ຠᯝࡣపࡃ⟬ฟࡉ ྛࣝࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ⓗ࡞ዲពᗘࡢᙳ ࢀࡸࡍ࠸ࠋࡋࡋࠊ᪥ᮏேࢆᑐ㇟ࡋࡓࣛࢸࣥ 㡪ಶேࡢᛂഴྥࡢᙳ㡪ࢆඹ⤫ไࡍࡿࡇ ࣝࣇ࣋ࢵࢺࡢዲࡳ㛵ࡍࡿ◊✲ࡣⓙ↓࡛࠶ ࡀᮃࡲࡋ࠸ࠋࡇ࠺ࡋࡓ⫼ᬒࢆ㋃ࡲ࠼࡚ࠊLeBel ࡿࡓࡵࠊᐇ㝿ࡇ࠺ࡋࡓၥ㢟ࡀ⏕ࡌࡿ࠺ & Gawronski(2009)ࡣࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢせ ࢆ᳨ウࡍࡿࡇࡣព⩏ࡀ࠶ࡿ࠸࠼ࡿࡔࢁ࠺ࠋ ࡞⟬ฟࣝࢦࣜࢬ࣒ 5 ࡘࢆẚ㍑ࡋࠊBaccus et ࡇࡢࡼ࠺ࠊ⌮ㄽୖࡣࡢ⟬ฟࣝࢦࣜࢬ࣒ al.(2004) ࡞ ࡛ ⏝ ࠸ ࡽ ࢀ ࡚ ࠸ ࡿ Ipsatized ࡶᴟ➃࡞ᚓⅬࡢ೫ࡾࡀ⏕ࡌࡓࡁࡣఱࡽࡢ double-correction algorithm: I-algorithm ࢆᙉ ၥ㢟ࢆ⏕ࡌ࠺ࡿࡀࠊᐇࢹ࣮ࢱࢆ⏝࠸࡚ࡇ࠺ࡋࡓ ࡃ᥎ዡࡋ࡚࠸ࡿࠋࡇࡢ⟬ฟࣝࢦࣜࢬ࣒ࡣୖ㏙ ၥ㢟ࢆ᳨ウࡋࡓ◊✲ࡣᮏ㑥࡛ࡣᑡ࡞࠸ࠋࡑࡇ࡛ ࡢ 2 ࡘࡢᙳ㡪ࢆྠ⤫ไࡍࡿࡇࢆ┠ⓗࡋ ᮏ◊✲࡛ࡣ㸪᪥ᮏேࢆᑐ㇟ࡋࡓࢽࢩࣕࣝ㑅 ࡚⪃ࡉࢀࡓࡶࡢ࡛ࠊ」ᩘࡢⅬ࡛ࡢࣝࢦࣜ ዲㄢ㢟ࡢࢹ࣮ࢱࢆ⏝࠸࡚ࠊ3 ࡘࡢ௦⾲ⓗ࡞ࢿ࣮ ࢬ࣒ࡼࡾࡶඃࢀ࡚࠸ࡿࡇࡀ♧ࡉࢀ࡚࠸ࡿࠋ࡞ ࣒ࣞࢱ࣮ຠᯝࡢ⟬ฟࣝࢦࣜࢬ࣒(B-algorithmࠊ － 66 － ネームレター効果の算出アルゴリズムの比較 S-algorithmࠊ I-algorithm)ࡢẚ㍑ࢆ⾜࠸ࠊᐇ 㝿ୖ㏙ࡢࡼ࠺࡞ၥ㢟ࡀ⏕ࡌࡿࡢ࠺ࢆ᫂ Table 1䚷䜲䝙䝅䝱䝹䛾ᗘᩘ A 23 74 ࡽࡋࡓୖ࡛ࠊ᭱ࡶ㐺ษ࡞⟬ฟࣝࢦࣜࢬ࣒ B 2 0 ࢆ≉ᐃࡍࡿࡇࢆ┠ⓗࡋࡓࠋ C 3 19 D 0 0 E 3 8 F 11 1 G 4 2 H 42 22 I 48 7 2㸬᪉ἲ (1)ㄪᰝᑐ㇟⪅ Ꮫ⏕ 521 ྡ㸦⏨ᛶ 81 ྡࠊዪᛶ 438 ྡࠊ ᫂ 2 ྡ㸧࡛ࠊᖹᆒᖺ㱋ࡣ 19.08 ṓ࡛࠶ࡗࡓࠋ (2)ㄪᰝෆᐜ J 0 1 K 69 50 ࣛࢸࣥࣝࣇ࣋ࢵࢺ 26 ᩥᏐࢆࣝࣇ࣋ L 0 0 ࢵࢺ㡰୪ࡓ⏝⣬ࢆ㓄ᕸࡋࠊࡑࢀࡒࢀࡢࣝ M 48 109 ࣇ࣋ࢵࢺᑐࡍࡿዲពᗘࢆࠕ1. ᎘࠸ࠖࠕ2. N 37 31 ࡞ࡾ᎘࠸ࠖࠕ3. ࡸࡸ᎘࠸ࠖࠕ4. ࡕࡽࡶ࠸ O 43 3 ࠼࡞࠸ࠖ ࠕ5. ࡸࡸዲࡁࠖ ࠕ6. ࡞ࡾዲࡁࠖ ࠕ7. P 0 0 ዲࡁࠖࡢ 7 ௳ἲ࡛ホᐃࡋ࡚ࡶࡽࡗࡓࠋᅇ⟅࠶ Q 0 0 ࡓࡗ࡚ࡣ┤ឤⓗᅇ⟅ࡍࡿࡼ࠺ᩍ♧ࡋࡓࠋ R 2 42 S 74 46 3㸬⤖ᯝ⪃ᐹ T 48 25 U 13 2 (1)ࣝࣇ࣋ࢵࢺࡈࡢࢽࢩࣕࣝࡢᗘᩘ V 0 0 ዲពᗘᖹᆒ W 5 1 ࣝࣇ࣋ࢵࢺࡈࠊࡑࡢࣝࣇ࣋ࢵࢺ X 0 0 ࢆࢽࢩࣕࣝࡶࡘேࡢᩘࢆࡲࡵࡓ(Table Y 46 76 1)ࠋࡲࡓࠊྛࣝࣇ࣋ࢵࢺࡢዲពᗘࢆࠊࡑࡢ Z 0 2 ᕥࡣⱑᏐࠊྑࡣྡ๓ࡢᗘᩘ ࣝࣇ࣋ࢵࢺࢆࢽࢩࣕࣝࡶࡓ࡞࠸ேࡓࡕ ࡢࢹ࣮ࢱࢆᖹᆒࡋ࡚⟬ฟࡋࡓ(Table 2)ࠋࡇࢀ ࡣࠊࡑࢀࡒࢀࡢࣝࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ⓗ ࡍࡿࡓࡵࠊࣝࣇ࣋ࢵࢺࡈࢿ࣮࣒ࣞࢱ࣮ ࡞ዲពᗘࢆ⾲ࡍࠋA ࡢዲពᗘࡀ᭱ࡶ㧗ࡗࡓࡀࠊ ຠᯝࡢࡁࡉࡀ␗࡞ࡿ࠺ࢆࠊ3 ࡘࡢࣝ ᖹᆒ್+1 ᶆ‽೫ᕪ௨ෆ࡛࠶ࡾࠊኳຠᯝࢆ⏕ ࢦࣜࢬ࣒ࡑࢀࡒࢀࡘ࠸࡚ㄪࡓࠋ ࡣࡌࡵࠊⱑᏐࡢࢽࢩࣕࣝ࠾ࡅࡿࢿ࣮࣒ ࡌࡿࡢ㧗ࡉ࡛ࡣ࡞࠸⪃࠼ࡽࢀࡿࠋ ࣞࢱ࣮ຠᯝࡘ࠸࡚ࡢ᳨ウࢆ⾜ࡗࡓࠋ (2)ྛࣝࣇ࣋ࢵࢺࡢ୍⯡ⓗዲពᗘ╔┠ࡋ B-algorithm ࡼࡗ࡚ࢿ࣮࣒ࣞࢱ࣮ຠᯝࢆ⟬ฟ ࡓศᯒ ࡋࠊ୍ඖ㓄⨨ࡢศᩓศᯒ࡛ࣝࣇ࣋ࢵࢺࡈ ࢿ࣮࣒ࣞࢱ࣮ຠᯝࢆẚ㍑ࡋࡓࠋࡑࡢ⤖ᯝࠊ ๓㏙ࡢࡢࡼ࠺ࠊ≉ᐃࡢࣝࣇ࣋ࢵࢺ ᑐࡍࡿ୍⯡ⓗዲពᗘࡀ㠀ᖖ㧗࠸ሙྜࠊ⟬ฟἲ ࣝࣇ࣋ࢵࢺࡢຠᯝࡣ᭷ព࡛ࡣ࡞ࡗࡓ(F(17, ࡼࡗ࡚ࡣࡑࡢࣝࣇ࣋ࢵࢺᑐࡍࡿࢿ࣮࣒ 503)=1.07, p=.38)ࠋS-algorithm ࡘ࠸࡚ࡶྠ ࣞࢱ࣮ຠᯝࡀ⏕ࡌࡃࡃ࡞ࡿࡇࡀ⪃࠼ࡽࢀࡿࠋ ᵝศᯒࢆ⾜ࡗࡓࡇࢁࠊࣝࣇ࣋ࢵࢺࡢຠ ୍᪉ࠊS-algorithm ࡛ࡣࠊ୍⯡ⓗዲࡲࢀࡸࡍ ᯝࡀ᭷ព࡛࠶ࡗࡓ(F(17, 503)=1.79, p=.03)ࠋ ࠸ࣝࣇ࣋ࢵࢺࢆࢽࢩࣕࣝࡶࡗ࡚࠸ࡿሙ Tukey ἲࡼࡿከ㔜ẚ㍑ࡢ⤖ᯝࠊAࠊKࠊM ࡢ ྜࠊᐇ㝿ࡢ₯ᅾⓗ⮬ᑛᚰ௨ୖࢿ࣮࣒ࣞࢱ࣮ຠ ࢿ࣮࣒ࣞࢱ࣮ຠᯝࡣࠊH ࡢࡑࢀࡼࡾࡶ᭷ព ᯝࡀ㧗ࡃ࡞ࡿྍ⬟ᛶࡀ࠶ࡿࠋࡇࡢၥ㢟ࢆ᳨ウ ࡁ࠸ࡇࡀ᫂ࡽ࡞ࡗࡓ(ࡑࢀࡒࢀ p =.00, － 67 － 愛知学泉大学・短期大学紀要 503)=2.15, p=.01)ࠊከ㔜ẚ㍑࡛ࡣ࠸ࡎࢀࡶ᭷ Table 2䚷ྛ䜰䝹䝣䜯䝧䝑䝖䛾୍⯡ⓗዲពᗘ 䠄䜲䝙䝅䝱䝹䛷䛿䛺䛔ሙྜ䛾ᖹᆒ䠅 A B ᖹᆒ ᶆ‽೫ᕪ 5.44 1.12 4.33 1.23 A ព࡞ᕪࡣࡳࡽࢀ࡞ࡗࡓࠋ௨ୖࡢศᯒ⤖ᯝࡣ ᖹᆒ ᶆ‽೫ᕪ 5.44 1.12 K 5.00 1.18 Table 3 ࡲࡵࡽࢀ࡚࠸ࡿࠋ ࡇࢀࡽࡢ⤖ᯝࢆ⥲ྜⓗゎ㔘ࡍࡿࠊ B-algorithm ࠾ࡼࡧ I-algorithm ࡛ࡣࣝࣇ C 4.25 1.15 S 4.89 1.35 D 4.14 1.18 R 4.77 1.32 E 4.29 1.21 N 4.60 1.29 ࡳࡽࢀ࡞ࡗࡓࠋࡘࡲࡾࠊ୍⯡ⓗዲពᗘࡀ㧗࠸ ࣋ࢵࢺࡢ㐪࠸ࡼࡿࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢ㐪࠸ࡣ F 4.14 1.13 M 4.59 1.37 㸦ప࠸㸧 ࡇࡼࡿࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢᙜ࡞ G 3.91 1.27 I 4.58 1.32 ᘬ㸦ቑ㸧ࡢྍ⬟ᛶࡣప࠸⪃࠼ࡽࢀࡿࠋ୍᪉ࠊ H 4.18 1.18 T 4.57 1.20 I 1.32 O S-algorithm ࡛ࡣࠊA ࡞ࡢ୍⯡ⓗዲពᗘࡀ㧗 4.58 4.52 1.29 J 4.48 1.31 J 4.48 1.31 ࠸ࣝࣇ࣋ࢵࢺ࠾ࡅࡿࢿ࣮࣒ࣞࢱ࣮ຠᯝࡀ K 5.00 1.18 P 4.42 1.20 L 4.38 1.19 Y 4.42 1.24 1.37 L 4.38 1.19 Table 2 ࡽࢃࡿࡼ࠺ࠊ᪥ᮏேࡣࠊAࠊKࠊ M 4.59 H ࡞ࡢ୍⯡ⓗዲពᗘࡀప࠸ࣝࣇ࣋ࢵࢺࡼ ࡾࡶࡁࡃ࡞ࡿഴྥࡀࡳࡽࢀࡓࠋTable 1 ࡸ N 4.60 1.29 X 4.36 1.36 SࠊRࠊMࠊN ࠸ࡗࡓ୍⯡ⓗዲពᗘࡀ㧗࠸ࣝ O 4.52 1.29 B 4.33 1.23 ࣇ࣋ࢵࢺࢆࢽࢩࣕࣝࡶࡘேࡀከ࠸ࡓࡵࠊ P 4.42 1.20 Z 4.30 1.33 ࡇࡢၥ㢟ࡀ⏕ࡌࡿ㢖ᗘࡣ㧗࠸ᛮࢃࢀࡿࠋࡋࡓ Q 4.09 1.32 E 4.29 1.21 R 4.77 1.32 C 4.25 1.15 ࡀࡗ࡚ࠊS-algorithm ࡢ㐺⏝ࡣ㑊ࡅࡓ࠺ࡀⰋ S 4.89 1.35 H 4.18 1.18 T 4.57 1.20 W 4.17 1.36 U 4.15 1.28 U 4.15 1.28 1.23 D 4.14 1.18 B-algorithm ࡣࠊࣝࣇ࣋ࢵࢺᑐࡍࡿ୍ V 4.11 ࠸ࡔࢁ࠺ࠋ (3)ಶேࡢᛂഴྥ╔┠ࡋࡓศᯒ W 4.17 1.36 F 4.14 1.13 ⯡ⓗዲពᗘ⮬㌟ࡢࢽࢩࣕࣝࡢホᐃ್ࡢࡳࢆ X 4.36 1.36 V 4.11 1.23 ィ⟬⏝࠸ࡿࠋࡑࡢࡓࡵࠊィ⟬ୖࡣࠊయⓗ Y 4.42 1.24 Q 4.09 1.32 Z 4.30 1.33 G 3.91 1.27 㧗࠸ዲពᗘホᐃࢆ⾜࠺ഴྥࡀ࠶ࡿಶேࡢࢿ࣮࣒ ᕥࡣࣝࣇ࣋ࢵࢺ㡰ࠊྑࡣᖹᆒ㡰ࢯ࣮ࢺࡋࡓࡶࡢ ࣞࢱ࣮ຠᯝࢆ㧗ࡃぢ✚ࡶࡿ୍᪉࡛ࠊయⓗప ࠸ዲពᗘホᐃࢆ⾜࠺ഴྥࡀ࠶ࡿಶேࡢࢿ࣮࣒ࣞ p=.00, p=.02)ࠋI-algorithm ࡘ࠸࡚ࡣࣝࣇ ࣋ ࢵ ࢺ ࡢ ຠ ᯝ ࡣ ᭷ ព ࡛ ࡣ ࡞ ࡗ ࡓ (F(17, 503)=0.98, p=.49)ࠋḟࠊྡ๓ࡢࢽࢩࣕࣝ ࢱ࣮ຠᯝࢆపࡃぢ✚ࡶࡿ࠸࠺ࣂࢫࡀ⏕ࡌ ࠾ࡅࡿࢿ࣮࣒ࣞࢱ࣮ຠᯝࡘ࠸࡚ࡢ᳨ウࢆ⾜ࡗ ࢩࣕࣝᑐࡍࡿዲពᗘࡢᖹᆒࢆồࡵࠊࡇࢀࢆಶ ࡓࠋ ࡉࡁྠᵝࡋ࡚ B-algorithm ࡘ ேࡢᛂഴྥࡋࡓࠋࡑࡋ࡚ࠊࢿ࣮࣒ࣞࢱ࣮ຠ ࠸࡚ศᯒࢆᐇࡋࡓࡇࢁࠊࣝࣇ࣋ࢵࢺࡢ ᯝࡢ┦㛵ಀᩘࢆ⟬ฟࣝࢦࣜࢬ࣒ࡈồࡵ ຠᯝࡀ᭷ព࡛࠶ࡗࡓ(F(14, 503)=2.07, p=.01)ࠋ ࡓ (Table 4) ࠋ ࡑ ࡢ ⤖ ᯝ ࠊ ண ࠾ ࡾ ࠊ ࡋࡋࠊTukey ἲࡼࡿከ㔜ẚ㍑ࡢ⤖ᯝࠊ࠸ࡎ B-algorithm ࠾࠸࡚㠀ࢽࢩࣕࣝࡢዲពᗘᖹ ࢀࡶ᭷ពᕪࡣࡳࡽࢀ࡞ࡗࡓࠋS-algorithm ᆒࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢ㛫᭷ព࡞ṇࡢ┦㛵 ࡛ࡶࣝࣇ࣋ࢵࢺࡢຠᯝࡣ᭷ព࡛࠶ࡗࡓ ࡀࡳࡽࢀࡓ(r=.34㹼.35, ࡍ࡚ p=.00)ࠋ ࠺ࡿࠋᐇ㝿ࡇ࠺ࡋࡓ⌧㇟ࡀ⏕ࡌ࡚࠸ࡿ࠺ ࢆ᳨ウࡍࡿࡓࡵࠊㄪᰝ༠ຊ⪅ࡈ㠀ࢽ (F(14, 503)=5.23, p=.00)ࠋከ㔜ẚ㍑ࡢ⤖ᯝࠊAࠊ ୍᪉ࠊS-algorithm I-algorithm ࡛ࡣࠊ㠀 NࠊR ࡣ C ࡼࡾࡶ㸦ࡑࢀࡒࢀ p=.00ࠊp=.02ࠊ ࢽࢩࣕࣝࡢዲពᗘᖹᆒࢿ࣮࣒ࣞࢱ࣮ຠᯝ p=.00㸧ࠊAࠊKࠊNࠊRࠊS ࡣ H ࡼࡾࡶ(ࡑࢀࡒ ࢀ p=.00, p=.04, p=.00, p=.00, p=.01)ࠊAࠊR ࡣ Y ࡼࡾࡶ(ࡍ࡚ p=.00)ࢿ࣮࣒ࣞࢱ࣮ຠᯝࡀ ࡢ┦㛵ࡣࡰⓙ↓࡛࠶ࡗࡓࠋS-algorithm ࡛ࡣ ᭷ពࡁࡗࡓࠋI-algorithm ࠾࠸࡚ࡶ ࡀࡕ࡞ಶேࡀᙜ㧗࠸㸦ప࠸㸧ࢿ࣮࣒ࣞࢱ࣮ ࣝࣇ࣋ࢵࢺࡢຠᯝࡣ᭷ព࡛࠶ࡗࡓࡀ(F(14, ຠᯝࢆ⋓ᚓࡋ࡚ࡋࡲ࠺࠸࠺⌧㇟ࡽண ࡉࢀ ࢃࡎ᭷ព࡞㈇ࡢ┦㛵ࡀࡳࡽࢀࡓࡀࠊࡇࢀࡣࠊ ࡢࡼ࠺࡞㉁ၥࡶ㧗࠸㸦ప࠸㸧ホᐃ್ࢆࡘࡅ － 68 － ネームレター効果の算出アルゴリズムの比較 Table 3䚷䜰䝹䝣䜯䝧䝑䝖䛻䜘䜛䝛䞊䝮䝺䝍䞊ຠᯝ䛾㐪䛔 family name Iirst name B-algorithm S-algorithm I-algorithm B-algorithm n.s. AࠊKࠊM>H n.s. n.s. S-algorithm I-algorithm AࠊNࠊR>C n.s. AࠊKࠊNࠊRࠊS>H A䚸R>Y ࡿ㛵ಀࡣ㏫ࡢ㛵ಀ࡛࠶ࡾࠊಶேࡢᛂഴྥ ࡗࡓࠋB-algorithm ࡸ S-algorithm ࡣィ⟬ࡀᐜ ⏤᮶ࡍࡿࢿ࣮࣒ࣞࢱ࣮ຠᯝࡢᙜ࡞ቑ㸦ᘬ㸧 ࡛᫆࠶ࡿ࠸࠺Ⅼࡀ࠶ࡿ㠃ࠊ⤫ィⓗ࡞ၥ㢟 ࡣࡳࡽࢀ࡞ࡗࡓ࠸࠼ࡿࠋ ࡶከ࠸⪃࠼ࡽࢀࡿࠋࡋࡓࡀࡗ࡚ࠊࢿ࣮࣒ࣞࢱ ࣮ຠᯝࡢ⟬ฟࡣ I-algorithm ࡢ⏝ࡀ᥎ዡࡉ ࡇࢀࡽࡢ⤖ᯝࢆࡲࡵࡿࠊB-algorithm ࢆ ⏝࠸ࡿಶேࡢᛂഴྥࡢᙳ㡪ࡼࡗ࡚ࢿ࣮࣒ ࢀࡿࠋ ࣞࢱ࣮ຠᯝࡢᙜ࡞ቑ㸦ᘬ㸧ࡀ⏕ࡌࡿࡀࠊ S-algorithm I-algorithm ࠾࠸࡚ࡣࡑ࠺ࡋ ᘬ⏝ᩥ⊩ ࡓಶேࡢᛂഴྥࡢᙳ㡪ࡣ↓ど࡛ࡁࡿ⪃࠼ࡽ 1) Alicke, M.D., & Olesya, G The ࢀࡿࠋ better-than-average effect. In M.D. Alicke, D.A. (4)ࡲࡵ judgment. Studies in self and identity. New York, Dunning, & J.I. Krueger(Eds.), The self in social NY: Psychology Press. pp. 85-106(2007) ᮏ◊✲࡛ࡣࠊྛࣝࣇ࣋ࢵࢺᑐࡍࡿ୍⯡ ࡽ࡞ࡗࡓࠋ୍᪉ࠊࡇࢀࡽ 2 ࡘࡢࣝࢦࣜࢬ 2) Baccus, J. R., Baldwin, M. W., & Packer, D. J. Increasing implicit self-esteem through classical conditioning. Psychological Science, 15, 498-502(2004) 3) Bosson, J. K., Swann, W .B., Jr., & Pennebaker, J. W. Stalking the perfect measure of implicit self-esteem: The blind men and the elephant revisited? Journal of Personality and Social Psychology, 79, 631-643(2000) ࣒ࡢḞⅬࢆᨵⰋࡋࡓ I-algorithm ࠾࠸࡚ࡣࠊ 4) Farnham, D. S., Greenwald, G. A., & Banaji, ⓗዲពᗘಶேࡢᛂഴྥ↔Ⅼࢆᙜ࡚࡚ࠊࢿ ࣮࣒ࣞࢱ࣮ຠᯝࡢせ࡞⟬ฟࣝࢦࣜࢬ࣒ࡢẚ ㍑᳨ウࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊྛࣝࣇ࣋ࢵࢺ ᑐࡍࡿ୍⯡ⓗዲពᗘ࠸࠺Ⅼ࡛ࡣ S-algorithm ၥ㢟ࡀ࠶ࡾࠊಶேࡢᛂഴྥ ࠸࠺Ⅼ࡛ࡣ B-algorithm ၥ㢟ࡀ࠶ࡿࡇࡀ᫂ ࠸ࡎࢀࡢⅬ࡛ࡶၥ㢟ࡣぢᙜࡓࡽ࡞ࡗࡓࠋ M.N. Implicit self-esteem. In D. Abrams, LeBel & Gawronski (2009)ࡶࠊࡉࡲࡊࡲ࡞ศᯒ & M. Hogg(Eds.), Social identity and social ࢆ㏻ࡌ࡚ I-algorithm ࡢ⏝ࢆ᥎ዡࡋ࡚࠸ࡿࠋ cognition. ᮏ◊✲ࡣࡇࢀࢆูࡢഃ㠃ࡽᨭᣢࡍࡿ⤖ᯝ࡞ pp.230-248(1999) Oxford, UK: Blackwell. Table 4ࠉࢽࢩࣕࣝࡢ㑅ዲຠᯝ㠀ࢽࢩࣕࣝࡢዲពᗘᖹᆒࡢ┦㛵 ձ ղ ճ ձB-algorithm (family name) Ɇ ղB-algorithm (first name) .30** Ɇ ճS-algorithm (family name) .89** .17** Ɇ մS-algorithm (first name) .15** յI-algorithm (family name) նI-algorithm (first name) շ㠀ࢽࢩࣕࣝࡢዲពᗘᖹᆒ մ յ .86** .20** Ɇ ** .17** .97** .20** ** .89** .21** .95** .91 .15 ** .34 ** .35 ** p <.01. * p <.05. － 69 － 䠉.07 * 䠉.10 ն Ɇ .21** 䠉.07 Ɇ * 䠉.11 愛知学泉大学・短期大学紀要 498-500(2007) 5) Greenwald, A. G., & Banaji, M. R. Implicit social cognition: Attitudes, self-esteem, Psychological stereotypes. and Review, 102, ὀ 4-27(1995) ᮏ◊✲ࡣࠊ⛉Ꮫ◊✲㈝⿵ຓ㔠㸦ⱝᡭ◊✲㸦B㸧 ࠊㄢ 㢟␒ྕ 25780432ࠊ◊✲௦⾲⪅ ὠ⏣ᜤ㸧ࡢຓ 6) Heine, S.J., Lehman, D.R., Markus, H.R., & Kitayama, S. Is there a universal need for positive self-regard? Psychological Review, 106, 766-794(1999) 7) Kitayama, S., & Karasawa, M. Implicit self-esteem in Japan: Name letters and birthday numbers. Personality and Social Psychology Bulletin, 23, 736-742(1997) 8) LeBel, E. P., & Gawronski, B. How to find what's in a name: Scrutinizing the optimality of five scoring algorithms for the name-letter task. European Journal of Personality, 23, 85-106(2009) 9) Miller, D. T., & Ross, M. Self-serving biases in the attribution of causality: Fact or fiction? Psychological Bulletin, 82, 213-225(1975) 10) Nuttin, J.M. Narcissism beyond Gestalt and awareness: The name letter effect. European Journal of Social Psychology, 15, 353-361(1985) 11) Nuttin, J.M. Affective consequences of mere ownership: The name-letter effect in twelve European languages. European Journal of Social Psychology, 15, 381-402(1987) 12) Stieger, S., Voracek, M., & Formann, A.K. How to administer the Initial Preference Task. European Journal of Personality, 26, 63-78(2012) 13) Taylor, S.E., & Brown, J.D. Positive illusions and well-being revisited: Separating fact from fiction. Psychological Bulletin, 116, 21-27(1994) 14) Taylor, S.E., & Brown, J. Illusion and well-being: A social psychological perspective on mental health. Psychological Bulletin, 103, 193-210(1988) 15) Yamaguchi, S., Greenwald, A.G., Banaji, M.R., Murakami, F., Chen, D., Shiomura, K., Kobayashi, C., Cai, H., & Krendl, A. Apparent Universality of Positive Implicit Self-Esteem. Psychological Science, 18, － 70 － ᡂࢆཷࡅࡓࠋ
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