心理学报 ›› 2025, Vol. 57 ›› Issue (4): 671-699.doi: 10.3724/SP.J.1041.2025.0671 cstr: 32110.14.2025.0671
收稿日期:
2023-12-02
发布日期:
2025-02-06
出版日期:
2025-04-25
通讯作者:
喻丰, E-mail: psychpedia@whu.edu.cn基金资助:
XU Liying, ZHANG Yuyan, YU Feng()
Received:
2023-12-02
Online:
2025-02-06
Published:
2025-04-25
摘要:
机器人进入社会可能会对人类造成心理威胁, 而这种威胁会给人际关系带来挑战。通过8个研究, 结合档案数据库回溯、问卷调查、情境实验和线下调查, 文章探讨了感知机器人威胁对亲社会倾向的影响及其内在机制和边界条件。结果发现:感知机器人威胁会降低人们的亲社会倾向(研究1~7); 其机制为集体焦虑的中介作用, 即感知机器人威胁会增加集体焦虑, 从而降低亲社会倾向(研究2~4); 此效应受到内外群体的调节, 即感知机器人威胁主要会降低对于外群体成员的亲社会倾向(研究5); 同时, 此效应受到道德比较倾向的调节, 即感知机器人威胁主要会降低下行道德比较者的亲社会倾向(研究6)。研究结果揭示了感知机器人威胁对人际关系的负面影响, 拓展了现有关于机器人社会影响的研究。
中图分类号:
许丽颖, 张语嫣, 喻丰. (2025). 感知机器人威胁降低亲社会倾向. 心理学报, 57(4), 671-699.
XU Liying, ZHANG Yuyan, YU Feng. (2025). Perceived robot threats reduce pro-social tendencies. Acta Psychologica Sinica, 57(4), 671-699.
研究 | 方法 | 实验设计 | 自变量测量/操纵 | 因变量 | 主要发现 | 样本 |
---|---|---|---|---|---|---|
1a | 档案数据库分析 | — | 感知机器人威胁量表 (the Eurobarometer 87.1, 2017) | 捐赠指数 (the Eurobarometer 87.1, 2017) | 感知机器人威胁与捐赠指数负相关。 | 27901 |
1b | 档案数据库分析 | — | 感知机器人威胁量表 (the Eurobarometer 77.1, 2012) | 对人道主义援助的支持 (the Eurobarometer 77.1, 2012) | 感知机器人威胁与对人道主义援助的支持负相关。 | 26751 |
2 | 问卷调查 | — | 感知机器人威胁量表 (Yogeeswaran et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁与亲社会倾向负相关, 集体焦虑在其中起中介作用。 | 148 |
3 | 线上实验 | 机器人威胁(高 vs. 低) | 视频操纵 (Yogeeswaran et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低亲社会倾向, 集体焦虑在其中起中介作用。 | 270 |
4 | 线上实验 | 机器人威胁(高 vs. 低) | 写作操纵 (许丽颖 等, | 亲社会倾向 (Touré-Tillery & Light, | 感知机器人威胁降低亲社会倾向, 集体焦虑在其中起中介作用。 | 270 |
5 | 线上实验 | 机器人威胁(高 vs. 低)×内外群体(内 vs.外) | 新闻网页图片操纵 (Jackson et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低对外群体的亲社会倾向, 但不会降低对内群体的亲社会倾向。 | 400 |
6 | 线上实验 | 机器人威胁(高 vs. 低) | 新闻网页图片操纵 (Jackson et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低道德下行比较者的亲社会倾向, 但不会降低道德上行比较者的亲社会倾向。 | 270 |
7 | 行为实验 | 机器人威胁(高 vs. 低) | 写作操纵 (许丽颖 等, | 给需要帮助的人写鼓励信(Gaesser et al., | 感知机器人威胁降低亲社会行为。 | 161 |
表1 研究总结
研究 | 方法 | 实验设计 | 自变量测量/操纵 | 因变量 | 主要发现 | 样本 |
---|---|---|---|---|---|---|
1a | 档案数据库分析 | — | 感知机器人威胁量表 (the Eurobarometer 87.1, 2017) | 捐赠指数 (the Eurobarometer 87.1, 2017) | 感知机器人威胁与捐赠指数负相关。 | 27901 |
1b | 档案数据库分析 | — | 感知机器人威胁量表 (the Eurobarometer 77.1, 2012) | 对人道主义援助的支持 (the Eurobarometer 77.1, 2012) | 感知机器人威胁与对人道主义援助的支持负相关。 | 26751 |
2 | 问卷调查 | — | 感知机器人威胁量表 (Yogeeswaran et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁与亲社会倾向负相关, 集体焦虑在其中起中介作用。 | 148 |
3 | 线上实验 | 机器人威胁(高 vs. 低) | 视频操纵 (Yogeeswaran et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低亲社会倾向, 集体焦虑在其中起中介作用。 | 270 |
4 | 线上实验 | 机器人威胁(高 vs. 低) | 写作操纵 (许丽颖 等, | 亲社会倾向 (Touré-Tillery & Light, | 感知机器人威胁降低亲社会倾向, 集体焦虑在其中起中介作用。 | 270 |
5 | 线上实验 | 机器人威胁(高 vs. 低)×内外群体(内 vs.外) | 新闻网页图片操纵 (Jackson et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低对外群体的亲社会倾向, 但不会降低对内群体的亲社会倾向。 | 400 |
6 | 线上实验 | 机器人威胁(高 vs. 低) | 新闻网页图片操纵 (Jackson et al., | 亲社会倾向 (Osgood & Muraven, | 感知机器人威胁降低道德下行比较者的亲社会倾向, 但不会降低道德上行比较者的亲社会倾向。 | 270 |
7 | 行为实验 | 机器人威胁(高 vs. 低) | 写作操纵 (许丽颖 等, | 给需要帮助的人写鼓励信(Gaesser et al., | 感知机器人威胁降低亲社会行为。 | 161 |
国家 | 样本量(N) | 性别(女性占比) | 年龄(M/SD) | |||||
---|---|---|---|---|---|---|---|---|
全部样本 | 劳动力样本 | 全部样本 | 劳动力样本 | 全部样本 | 劳动力样本 | |||
1 | 法国 | 1004 | 412 | 56.37% | 52.40% | 52.13 (19.06) | 42.19 (11.85) | |
2 | 比利时 | 1023 | 430 | 51.22% | 50.00% | 52.64 (19.01) | 43.81 (11.98) | |
3 | 荷兰 | 1015 | 544 | 49.75% | 48.70% | 52.41 (16.39) | 47.36 (12.12) | |
4 | 德国 | 1537 | 650 | 49.19% | 50.70% | 54.07 (19.39) | 44.49 (12.22) | |
5 | 意大利 | 1022 | 471 | 54.01% | 54.00% | 49.3 (17.29) | 45.72 (10.50) | |
6 | 卢森堡 | 510 | 221 | 52.75% | 52.70% | 50.87 (18.53) | 43.13 (11.51) | |
7 | 丹麦 | 1000 | 495 | 50.30% | 49.90% | 55.58 (17.87) | 48.52 (11.94) | |
8 | 爱尔兰 | 1021 | 509 | 51.91% | 47.90% | 48.60 (17.50) | 43.62 (12.01) | |
9 | 英国 | 1346 | 620 | 50.45% | 50.40% | 53.27 (19.63) | 43.40 (13.76) | |
10 | 希腊 | 1010 | 442 | 52.18% | 45.50% | 49.37 (17.97) | 43.24 (12.06) | |
11 | 西班牙 | 1024 | 408 | 51.37% | 45.60% | 49.87 (18.43) | 42.67 (11.49) | |
12 | 葡萄牙 | 1061 | 600 | 55.80% | 55.20% | 49.64 (18.01) | 43.07 (11.92) | |
13 | 芬兰 | 1012 | 403 | 53.95% | 52.30% | 55.33 (18.89) | 45.38 (12.77) | |
14 | 瑞典 | 1007 | 507 | 42.80% | 40.80% | 58.02 (17.24) | 48.64 (13.52) | |
15 | 奥地利 | 1001 | 588 | 52.85% | 50.90% | 48.80 (16.96) | 42.31 (11.58) | |
16 | 塞浦路斯 | 501 | 233 | 52.30% | 46.40% | 51.00 (18.16) | 44.16 (11.70) | |
17 | 捷克共和国 | 1058 | 621 | 60.11% | 55.90% | 47.77 (16.64) | 43.55 (11.58) | |
18 | 爱沙尼亚 | 1017 | 489 | 64.70% | 60.90% | 56.16 (18.31) | 47.34 (12.27) | |
19 | 匈牙利 | 1053 | 525 | 56.98% | 49.70% | 52.76 (17.60) | 43.55 (11.72) | |
20 | 拉脱维亚 | 1004 | 493 | 62.05% | 61.30% | 48.64 (17.35) | 44.67 (13.62) | |
21 | 立陶宛 | 1001 | 404 | 64.24% | 57.20% | 55.66 (19.10) | 45.00 (12.86) | |
22 | 马耳他 | 500 | 187 | 57.80% | 48.70% | 54.85 (19.00) | 43.72 (14.35) | |
23 | 波兰 | 1008 | 514 | 59.23% | 55.30% | 48.74 (17.30) | 42.08 (11.68) | |
24 | 斯洛伐克 | 1014 | 481 | 60.45% | 56.80% | 51.21 (17.53) | 43.41 (11.40) | |
25 | 斯洛文尼亚 | 1027 | 438 | 59.69% | 55.70% | 52.95 (18.55) | 43.89 (11.59) | |
26 | 保加利亚 | 1044 | 589 | 53.07% | 52.10% | 48.95 (16.82) | 43.83 (11.14) | |
27 | 罗马利亚 | 1033 | 528 | 56.53% | 49.20% | 45.17 (16.58) | 40.14 (11.02) | |
28 | 克罗地亚 | 1048 | 492 | 60.21% | 58.30% | 44.84 (17.11) | 40.13 (11.05) | |
总计 | 27, 901 | 13, 294 | 54.97% | 51.50% | 51.3 8(18.25) | 44.06 (12.20) |
表2 国家层面的人口统计信息: 性别和年龄
国家 | 样本量(N) | 性别(女性占比) | 年龄(M/SD) | |||||
---|---|---|---|---|---|---|---|---|
全部样本 | 劳动力样本 | 全部样本 | 劳动力样本 | 全部样本 | 劳动力样本 | |||
1 | 法国 | 1004 | 412 | 56.37% | 52.40% | 52.13 (19.06) | 42.19 (11.85) | |
2 | 比利时 | 1023 | 430 | 51.22% | 50.00% | 52.64 (19.01) | 43.81 (11.98) | |
3 | 荷兰 | 1015 | 544 | 49.75% | 48.70% | 52.41 (16.39) | 47.36 (12.12) | |
4 | 德国 | 1537 | 650 | 49.19% | 50.70% | 54.07 (19.39) | 44.49 (12.22) | |
5 | 意大利 | 1022 | 471 | 54.01% | 54.00% | 49.3 (17.29) | 45.72 (10.50) | |
6 | 卢森堡 | 510 | 221 | 52.75% | 52.70% | 50.87 (18.53) | 43.13 (11.51) | |
7 | 丹麦 | 1000 | 495 | 50.30% | 49.90% | 55.58 (17.87) | 48.52 (11.94) | |
8 | 爱尔兰 | 1021 | 509 | 51.91% | 47.90% | 48.60 (17.50) | 43.62 (12.01) | |
9 | 英国 | 1346 | 620 | 50.45% | 50.40% | 53.27 (19.63) | 43.40 (13.76) | |
10 | 希腊 | 1010 | 442 | 52.18% | 45.50% | 49.37 (17.97) | 43.24 (12.06) | |
11 | 西班牙 | 1024 | 408 | 51.37% | 45.60% | 49.87 (18.43) | 42.67 (11.49) | |
12 | 葡萄牙 | 1061 | 600 | 55.80% | 55.20% | 49.64 (18.01) | 43.07 (11.92) | |
13 | 芬兰 | 1012 | 403 | 53.95% | 52.30% | 55.33 (18.89) | 45.38 (12.77) | |
14 | 瑞典 | 1007 | 507 | 42.80% | 40.80% | 58.02 (17.24) | 48.64 (13.52) | |
15 | 奥地利 | 1001 | 588 | 52.85% | 50.90% | 48.80 (16.96) | 42.31 (11.58) | |
16 | 塞浦路斯 | 501 | 233 | 52.30% | 46.40% | 51.00 (18.16) | 44.16 (11.70) | |
17 | 捷克共和国 | 1058 | 621 | 60.11% | 55.90% | 47.77 (16.64) | 43.55 (11.58) | |
18 | 爱沙尼亚 | 1017 | 489 | 64.70% | 60.90% | 56.16 (18.31) | 47.34 (12.27) | |
19 | 匈牙利 | 1053 | 525 | 56.98% | 49.70% | 52.76 (17.60) | 43.55 (11.72) | |
20 | 拉脱维亚 | 1004 | 493 | 62.05% | 61.30% | 48.64 (17.35) | 44.67 (13.62) | |
21 | 立陶宛 | 1001 | 404 | 64.24% | 57.20% | 55.66 (19.10) | 45.00 (12.86) | |
22 | 马耳他 | 500 | 187 | 57.80% | 48.70% | 54.85 (19.00) | 43.72 (14.35) | |
23 | 波兰 | 1008 | 514 | 59.23% | 55.30% | 48.74 (17.30) | 42.08 (11.68) | |
24 | 斯洛伐克 | 1014 | 481 | 60.45% | 56.80% | 51.21 (17.53) | 43.41 (11.40) | |
25 | 斯洛文尼亚 | 1027 | 438 | 59.69% | 55.70% | 52.95 (18.55) | 43.89 (11.59) | |
26 | 保加利亚 | 1044 | 589 | 53.07% | 52.10% | 48.95 (16.82) | 43.83 (11.14) | |
27 | 罗马利亚 | 1033 | 528 | 56.53% | 49.20% | 45.17 (16.58) | 40.14 (11.02) | |
28 | 克罗地亚 | 1048 | 492 | 60.21% | 58.30% | 44.84 (17.11) | 40.13 (11.05) | |
总计 | 27, 901 | 13, 294 | 54.97% | 51.50% | 51.3 8(18.25) | 44.06 (12.20) |
国家 | 亲社会行为指数(%) | ln (GDP) | Gini指数 | ||||
---|---|---|---|---|---|---|---|
捐赠指数 | 帮助他人 | 金钱捐赠 | 时间付出 | ||||
1 | 法国 | 33 | 39 | 30 | 31 | 10.52 | 31.90 |
2 | 比利时 | 35 | 46 | 34 | 26 | 10.65 | 27.60 |
3 | 荷兰 | 51 | 51 | 64 | 36 | 10.74 | 28.20 |
4 | 德国 | 45 | 58 | 55 | 22 | 10.65 | 31.40 |
5 | 意大利 | 30 | 44 | 30 | 15 | 10.34 | 35.20 |
6 | 卢森堡 | 38 | 37 | 48 | 28 | 11.58 | 31.70 |
7 | 丹麦 | 44 | 57 | 54 | 21 | 10.91 | 28.20 |
8 | 爱尔兰 | 53 | 61 | 60 | 39 | 11.05 | 32.80 |
9 | 英国 | 50 | 58 | 64 | 28 | 10.62 | 33.10 |
10 | 希腊 | 24 | 50 | 10 | 11 | 9.79 | 35.00 |
11 | 西班牙 | 33 | 51 | 33 | 14 | 10.19 | 35.80 |
12 | 葡萄牙 | 26 | 46 | 14 | 17 | 9.90 | 35.20 |
13 | 芬兰 | 40 | 55 | 37 | 28 | 10.69 | 27.10 |
14 | 瑞典 | 41 | 53 | 55 | 14 | 10.86 | 29.60 |
15 | 奥地利 | 42 | 51 | 48 | 28 | 10.72 | 30.80 |
16 | 塞浦路斯 | 38 | 54 | 34 | 24 | 10.12 | 32.90 |
17 | 捷克共和国 | 18 | 23 | 18 | 14 | 9.83 | 25.40 |
18 | 爱沙尼亚 | 27 | 36 | 22 | 22 | 9.81 | 31.60 |
19 | 匈牙利 | 21 | 36 | 17 | 9 | 9.48 | 30.30 |
20 | 拉脱维亚 | 18 | 28 | 20 | 5 | 9.57 | 34.30 |
21 | 立陶宛 | 16 | 28 | 10 | 10 | 9.62 | 38.40 |
22 | 马耳他 | 48 | 45 | 73 | 26 | 10.15 | 29.10 |
23 | 波兰 | 26 | 37 | 27 | 13 | 9.42 | 31.20 |
24 | 斯洛伐克 | 26 | 33 | 30 | 16 | 9.71 | 25.20 |
25 | 斯洛文尼亚 | 34 | 40 | 32 | 32 | 9.98 | 24.80 |
26 | 保加利亚 | 19 | 34 | 17 | 5 | 8.93 | 40.60 |
27 | 罗马利亚 | 31 | 60 | 24 | 9 | 9.15 | 34.40 |
28 | 克罗地亚 | 20 | 21 | 28 | 12 | 9.44 | 30.90 |
表3 亲社会行为指标与国家层面的控制变量
国家 | 亲社会行为指数(%) | ln (GDP) | Gini指数 | ||||
---|---|---|---|---|---|---|---|
捐赠指数 | 帮助他人 | 金钱捐赠 | 时间付出 | ||||
1 | 法国 | 33 | 39 | 30 | 31 | 10.52 | 31.90 |
2 | 比利时 | 35 | 46 | 34 | 26 | 10.65 | 27.60 |
3 | 荷兰 | 51 | 51 | 64 | 36 | 10.74 | 28.20 |
4 | 德国 | 45 | 58 | 55 | 22 | 10.65 | 31.40 |
5 | 意大利 | 30 | 44 | 30 | 15 | 10.34 | 35.20 |
6 | 卢森堡 | 38 | 37 | 48 | 28 | 11.58 | 31.70 |
7 | 丹麦 | 44 | 57 | 54 | 21 | 10.91 | 28.20 |
8 | 爱尔兰 | 53 | 61 | 60 | 39 | 11.05 | 32.80 |
9 | 英国 | 50 | 58 | 64 | 28 | 10.62 | 33.10 |
10 | 希腊 | 24 | 50 | 10 | 11 | 9.79 | 35.00 |
11 | 西班牙 | 33 | 51 | 33 | 14 | 10.19 | 35.80 |
12 | 葡萄牙 | 26 | 46 | 14 | 17 | 9.90 | 35.20 |
13 | 芬兰 | 40 | 55 | 37 | 28 | 10.69 | 27.10 |
14 | 瑞典 | 41 | 53 | 55 | 14 | 10.86 | 29.60 |
15 | 奥地利 | 42 | 51 | 48 | 28 | 10.72 | 30.80 |
16 | 塞浦路斯 | 38 | 54 | 34 | 24 | 10.12 | 32.90 |
17 | 捷克共和国 | 18 | 23 | 18 | 14 | 9.83 | 25.40 |
18 | 爱沙尼亚 | 27 | 36 | 22 | 22 | 9.81 | 31.60 |
19 | 匈牙利 | 21 | 36 | 17 | 9 | 9.48 | 30.30 |
20 | 拉脱维亚 | 18 | 28 | 20 | 5 | 9.57 | 34.30 |
21 | 立陶宛 | 16 | 28 | 10 | 10 | 9.62 | 38.40 |
22 | 马耳他 | 48 | 45 | 73 | 26 | 10.15 | 29.10 |
23 | 波兰 | 26 | 37 | 27 | 13 | 9.42 | 31.20 |
24 | 斯洛伐克 | 26 | 33 | 30 | 16 | 9.71 | 25.20 |
25 | 斯洛文尼亚 | 34 | 40 | 32 | 32 | 9.98 | 24.80 |
26 | 保加利亚 | 19 | 34 | 17 | 5 | 8.93 | 40.60 |
27 | 罗马利亚 | 31 | 60 | 24 | 9 | 9.15 | 34.40 |
28 | 克罗地亚 | 20 | 21 | 28 | 12 | 9.44 | 30.90 |
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | ||||||||||||||||||||||||||||||||||||||||||||||||
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1 | 性别 | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 年龄 | −0.012* | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 社区 | −0.01 | −0.037*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 教育 | 0.01 | −0.103*** | 0.124*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
5 | 政治取向 | 0.021** | 0.020*** | 0.00 | −0.021** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
6 | 技术技能a | 0.056*** | −0.457*** | 0.072*** | 0.308*** | 0.00 | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
7 | 技术技能b | 0.00 | −0.181*** | 0.072*** | 0.277*** | −0.01 | 0.762*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
8 | 技术技能c | 0.052*** | −0.324*** | 0.082*** | 0.276*** | −0.01 | 0.738*** | 0.724*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
9 | 工作被 替代 | 0.059*** | −0.077*** | 0.044*** | −0.051*8* | 0.024* | 0.01 | 0.00 | 0.026** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
10 | 相关了解 | −0.101*** | 0.130*** | −0.062*** | −0.273*** | 0.027*** | −0.334*** | −0.290*** | −0.289*** | −0.030** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
11 | 机器人 使用a | 0.00 | 0.080*** | −0.021*** | −0.080*** | −0.016* | −0.123*** | −0.089*** | −0.097*** | −0.085*** | 0.121*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
12 | 机器人 使用b | −0.095*** | 0.072*** | −0.013* | −0.057*** | −0.017* | −0.091*** | −0.079*** | −0.082*** | −0.133*** | 0.115*** | 0.129*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
13 | 机器人 使用c | −0.030*** | 0.063*** | −0.026*** | −0.031*** | 0.00 | −0.043*** | −0.018* | −0.039*** | −0.061*** | 0.058*** | 0.043*** | 0.058*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
14 | 社会阶层 | 0.01 | −0.083*** | 0.114*** | 0.311*** | 0.061*** | 0.270*** | 0.240*** | 0.238*** | −0.061*** | −0.225*** | −0.110*** | −0.056*** | −0.035*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
15 | Gini系数 | 0.00 | −0.044*** | 0.087*** | −0.136*** | 0.01 | −0.063*** | −0.065*** | −0.060*** | 0.067*** | 0.153*** | 0.062*** | 0.062*** | 0.019** | −0.159*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
16 | ln GDP | 0.065*** | 0.081*** | −0.033*** | 0.142*** | −0.071*** | 0.154*** | 0.180*** | 0.156*** | −0.101*** | −0.224*** | −0.056*** | −0.056*** | −0.018** | 0.173*** | −0.336*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
17 | 机器人 威胁a | −0.065*** | 0.025*** | −0.048*** | −0.139*** | −0.027*** | −0.116*** | −0.096*** | −0.089*** | 0.036*** | 0.119*** | 0.050*** | 0.054*** | 0.038*** | −0.149*** | 0.134*** | −0.091*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
18 | 机器人 威胁b | −0.053*** | 0.073*** | −0.030*** | −0.127*** | −0.015* | −0.226*** | −0.203*** | −0.204*** | −0.123*** | 0.146*** | 0.111*** | 0.070*** | 0.024*** | −0.092*** | 0.01 | 0.034*** | 0.102*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
19 | 机器人 威胁c | 0.01 | 0.030*** | 0.00 | 0.080*** | −0.018** | 0.101*** | 0.132*** | 0.094*** | −0.033*** | −0.155*** | 0.01 | 0.00 | 0.029*** | 0.00 | 0.025*** | 0.075*** | 0.216*** | −0.213*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||
20 | 机器人 威胁d | −0.051*** | 0.00 | −0.018** | −0.116*** | −0.01 | −0.179*** | −0.192*** | −0.164*** | −0.052*** | 0.184*** | 0.059*** | 0.047*** | 0.00 | −0.052*** | 0.00 | −0.012* | −0.017** | 0.472*** | −0.376*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||
21 | 机器人 威胁e | −0.069*** | 0.050*** | −0.058*** | −0.185*** | −0.01 | −0.162*** | −0.157*** | −0.141*** | 0.045*** | 0.169*** | 0.054*** | 0.070*** | 0.030*** | −0.189*8* | 0.171*** | −0.126*** | 0.638*** | 0.159*** | 0.158*** | 0.044*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||
22 | 机器人威胁指标 | −0.072*** | 0.041*** | −0.058*** | −0.177*** | −0.020** | −0.152*** | −0.141*** | −0.127*** | 0.046*** | 0.157*** | 0.056*** | 0.067*** | 0.036*** | −0.186*** | 0.167*** | −0.119*** | 0.902*** | 0.145*** | 0.202*** | 0.017** | 0.912*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||
23 | 机器人威胁指标 | −0.084*** | 0.069*** | −0.057*** | −0.188*** | −0.026*** | −0.222*** | −0.203*** | −0.193*** | −0.041*** | 0.182*** | 0.100*** | 0.087*** | 0.045*** | −0.179*** | 0.130*** | −0.053*** | 0.719*** | 0.578*** | 0.238*** | 0.423*** | 0.750*** | 0.807*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||
24 | 帮助他人 | 0.076*** | 0.045*** | −0.014* | 0.068*** | −0.067*** | 0.097*** | 0.108*** | 0.082*** | −0.043*** | −0.086*** | 0.00 | −0.027*** | −0.017** | 0.066*** | 0.020** | 0.580*** | −0.050*** | 0.028*** | 0.045*** | 0.017** | −0.071*** | −0.065*** | −0.014* | — | ||||||||||||||||||||||||||||||||||||||||||||||||||
25 | 金钱捐赠 | 0.064**8* | 0.063*** | −0.057*** | 0.119*** | −0.073*** | 0.162*** | 0.198*** | 0.164*** | −0.093*** | −0.176*** | −0.025*** | −0.035*** | 0.00 | 0.150*** | −0.320*** | 0.759*** | −0.115*** | −0.01 | 0.051*** | −0.027*** | −0.159*** | −0.151*** | −0.102*** | 0.625*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||
26 | 时间付出 | 0.031*** | 0.053*** | −0.070*** | 0.050*** | −0.058*** | 0.106*** | 0.136*** | 0.129*** | −0.090*** | −0.162*** | −0.014* | −0.039*** | −0.01 | 0.114*** | −0.445*** | 0.755*** | −0.057*** | 0.062*** | 0.036*** | 0.023*** | −0.094*** | −0.083*** | −0.017** | 0.473*** | 0.681*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||
27 | 捐赠指数 | 0.070*** | 0.065*** | −0.053*** | 0.101*** | −0.077*** | 0.150*** | 0.180*** | 0.151*** | −0.089*** | −0.169*** | −0.017** | −0.038*** | −0.01 | 0.134*** | −0.272*** | 0.812*** | −0.094*** | 0.023*** | 0.055*** | 0.00 | −0.134*** | −0.125*** | −0.063*** | 0.817*** | 0.935*** | 0.795*** | — | |||||||||||||||||||||||||||||||||||||||||||||||
M | 51.38 | 1.95 | 19.66 | 5.28 | 2.89 | 3.18 | 2.99 | 1.71 | 0.53 | 0.93 | 0.95 | 0.98 | 2.35 | 31.56 | 10.14 | 3.16 | 2.09 | 3.49 | 1.70 | 3.09 | 3.12 | 2.71 | 33.00 | 44.29 | 34.98 | 19.57 | |||||||||||||||||||||||||||||||||||||||||||||||||
SD | 18.25 | 0.77 | 5.23 | 2.18 | 1.07 | 0.92 | 0.96 | 0.88 | 0.50 | 0.26 | 0.22 | 0.13 | 0.99 | 3.83 | 0.61 | 0.85 | 0.84 | 0.67 | 0.77 | 0.89 | 0.79 | 0.47 | 11.00 | 11.59 | 17.38 | 9.25 |
表4 全部样本: 相关性与描述性数据
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | ||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 性别 | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 年龄 | −0.012* | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 社区 | −0.01 | −0.037*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 教育 | 0.01 | −0.103*** | 0.124*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
5 | 政治取向 | 0.021** | 0.020*** | 0.00 | −0.021** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
6 | 技术技能a | 0.056*** | −0.457*** | 0.072*** | 0.308*** | 0.00 | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
7 | 技术技能b | 0.00 | −0.181*** | 0.072*** | 0.277*** | −0.01 | 0.762*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
8 | 技术技能c | 0.052*** | −0.324*** | 0.082*** | 0.276*** | −0.01 | 0.738*** | 0.724*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
9 | 工作被 替代 | 0.059*** | −0.077*** | 0.044*** | −0.051*8* | 0.024* | 0.01 | 0.00 | 0.026** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
10 | 相关了解 | −0.101*** | 0.130*** | −0.062*** | −0.273*** | 0.027*** | −0.334*** | −0.290*** | −0.289*** | −0.030** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
11 | 机器人 使用a | 0.00 | 0.080*** | −0.021*** | −0.080*** | −0.016* | −0.123*** | −0.089*** | −0.097*** | −0.085*** | 0.121*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
12 | 机器人 使用b | −0.095*** | 0.072*** | −0.013* | −0.057*** | −0.017* | −0.091*** | −0.079*** | −0.082*** | −0.133*** | 0.115*** | 0.129*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
13 | 机器人 使用c | −0.030*** | 0.063*** | −0.026*** | −0.031*** | 0.00 | −0.043*** | −0.018* | −0.039*** | −0.061*** | 0.058*** | 0.043*** | 0.058*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
14 | 社会阶层 | 0.01 | −0.083*** | 0.114*** | 0.311*** | 0.061*** | 0.270*** | 0.240*** | 0.238*** | −0.061*** | −0.225*** | −0.110*** | −0.056*** | −0.035*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
15 | Gini系数 | 0.00 | −0.044*** | 0.087*** | −0.136*** | 0.01 | −0.063*** | −0.065*** | −0.060*** | 0.067*** | 0.153*** | 0.062*** | 0.062*** | 0.019** | −0.159*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
16 | ln GDP | 0.065*** | 0.081*** | −0.033*** | 0.142*** | −0.071*** | 0.154*** | 0.180*** | 0.156*** | −0.101*** | −0.224*** | −0.056*** | −0.056*** | −0.018** | 0.173*** | −0.336*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
17 | 机器人 威胁a | −0.065*** | 0.025*** | −0.048*** | −0.139*** | −0.027*** | −0.116*** | −0.096*** | −0.089*** | 0.036*** | 0.119*** | 0.050*** | 0.054*** | 0.038*** | −0.149*** | 0.134*** | −0.091*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
18 | 机器人 威胁b | −0.053*** | 0.073*** | −0.030*** | −0.127*** | −0.015* | −0.226*** | −0.203*** | −0.204*** | −0.123*** | 0.146*** | 0.111*** | 0.070*** | 0.024*** | −0.092*** | 0.01 | 0.034*** | 0.102*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
19 | 机器人 威胁c | 0.01 | 0.030*** | 0.00 | 0.080*** | −0.018** | 0.101*** | 0.132*** | 0.094*** | −0.033*** | −0.155*** | 0.01 | 0.00 | 0.029*** | 0.00 | 0.025*** | 0.075*** | 0.216*** | −0.213*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||||
20 | 机器人 威胁d | −0.051*** | 0.00 | −0.018** | −0.116*** | −0.01 | −0.179*** | −0.192*** | −0.164*** | −0.052*** | 0.184*** | 0.059*** | 0.047*** | 0.00 | −0.052*** | 0.00 | −0.012* | −0.017** | 0.472*** | −0.376*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||||
21 | 机器人 威胁e | −0.069*** | 0.050*** | −0.058*** | −0.185*** | −0.01 | −0.162*** | −0.157*** | −0.141*** | 0.045*** | 0.169*** | 0.054*** | 0.070*** | 0.030*** | −0.189*8* | 0.171*** | −0.126*** | 0.638*** | 0.159*** | 0.158*** | 0.044*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||
22 | 机器人威胁指标 | −0.072*** | 0.041*** | −0.058*** | −0.177*** | −0.020** | −0.152*** | −0.141*** | −0.127*** | 0.046*** | 0.157*** | 0.056*** | 0.067*** | 0.036*** | −0.186*** | 0.167*** | −0.119*** | 0.902*** | 0.145*** | 0.202*** | 0.017** | 0.912*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||
23 | 机器人威胁指标 | −0.084*** | 0.069*** | −0.057*** | −0.188*** | −0.026*** | −0.222*** | −0.203*** | −0.193*** | −0.041*** | 0.182*** | 0.100*** | 0.087*** | 0.045*** | −0.179*** | 0.130*** | −0.053*** | 0.719*** | 0.578*** | 0.238*** | 0.423*** | 0.750*** | 0.807*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||
24 | 帮助他人 | 0.076*** | 0.045*** | −0.014* | 0.068*** | −0.067*** | 0.097*** | 0.108*** | 0.082*** | −0.043*** | −0.086*** | 0.00 | −0.027*** | −0.017** | 0.066*** | 0.020** | 0.580*** | −0.050*** | 0.028*** | 0.045*** | 0.017** | −0.071*** | −0.065*** | −0.014* | — | ||||||||||||||||||||||||||||||||||||||||||||||||||
25 | 金钱捐赠 | 0.064**8* | 0.063*** | −0.057*** | 0.119*** | −0.073*** | 0.162*** | 0.198*** | 0.164*** | −0.093*** | −0.176*** | −0.025*** | −0.035*** | 0.00 | 0.150*** | −0.320*** | 0.759*** | −0.115*** | −0.01 | 0.051*** | −0.027*** | −0.159*** | −0.151*** | −0.102*** | 0.625*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||
26 | 时间付出 | 0.031*** | 0.053*** | −0.070*** | 0.050*** | −0.058*** | 0.106*** | 0.136*** | 0.129*** | −0.090*** | −0.162*** | −0.014* | −0.039*** | −0.01 | 0.114*** | −0.445*** | 0.755*** | −0.057*** | 0.062*** | 0.036*** | 0.023*** | −0.094*** | −0.083*** | −0.017** | 0.473*** | 0.681*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||
27 | 捐赠指数 | 0.070*** | 0.065*** | −0.053*** | 0.101*** | −0.077*** | 0.150*** | 0.180*** | 0.151*** | −0.089*** | −0.169*** | −0.017** | −0.038*** | −0.01 | 0.134*** | −0.272*** | 0.812*** | −0.094*** | 0.023*** | 0.055*** | 0.00 | −0.134*** | −0.125*** | −0.063*** | 0.817*** | 0.935*** | 0.795*** | — | |||||||||||||||||||||||||||||||||||||||||||||||
M | 51.38 | 1.95 | 19.66 | 5.28 | 2.89 | 3.18 | 2.99 | 1.71 | 0.53 | 0.93 | 0.95 | 0.98 | 2.35 | 31.56 | 10.14 | 3.16 | 2.09 | 3.49 | 1.70 | 3.09 | 3.12 | 2.71 | 33.00 | 44.29 | 34.98 | 19.57 | |||||||||||||||||||||||||||||||||||||||||||||||||
SD | 18.25 | 0.77 | 5.23 | 2.18 | 1.07 | 0.92 | 0.96 | 0.88 | 0.50 | 0.26 | 0.22 | 0.13 | 0.99 | 3.83 | 0.61 | 0.85 | 0.84 | 0.67 | 0.77 | 0.89 | 0.79 | 0.47 | 11.00 | 11.59 | 17.38 | 9.25 |
变量 | 回归系数与 显著性 | 变量 | 回归系数与 显著性 |
---|---|---|---|
(常量) | −121.36(1.111) | (常量) | −121.70(1.119) |
性别 | 0.38***(0.090) | 性别 | 0.38***(0.090) |
年龄 | 0.01***(0.003) | 年龄 | 0.01**(0.003) |
社区 | −0.35***(0.058) | 社区 | −0.34***(0.058) |
教育 | −0.04***(0.009) | 教育 | −0.04***(0.009) |
政治取向 | −0.11***(0.021) | 政治取向 | −0.11***(0.021) |
技术技能a | 0.43***(0.052) | 技术技能a | 0.41***(0.052) |
相关了解 | 0.29**(0.098) | 相关了解 | 0.29**(0.098) |
机器人使用a | 1.35***(0.167) | 机器人使用a | 1.40***(0.167) |
机器人使用c | 0.28(0.338) | 机器人使用c | 0.31(0.338) |
社会阶层 | −0.01(0.050) | 社会阶层 | 0.00(0.050) |
Gini系数 | 0.06***(0.013) | Gini系数 | 0.06***(0.013) |
ln GDP | 15.03***(0.081) | ln GDP | 15.07***(0.080) |
机器人威胁指标1 | −0.51***(0.059) | 机器人威胁指标2 | −0.60***(0.102) |
表5 全部样本中的机器人威胁与亲社会行为
变量 | 回归系数与 显著性 | 变量 | 回归系数与 显著性 |
---|---|---|---|
(常量) | −121.36(1.111) | (常量) | −121.70(1.119) |
性别 | 0.38***(0.090) | 性别 | 0.38***(0.090) |
年龄 | 0.01***(0.003) | 年龄 | 0.01**(0.003) |
社区 | −0.35***(0.058) | 社区 | −0.34***(0.058) |
教育 | −0.04***(0.009) | 教育 | −0.04***(0.009) |
政治取向 | −0.11***(0.021) | 政治取向 | −0.11***(0.021) |
技术技能a | 0.43***(0.052) | 技术技能a | 0.41***(0.052) |
相关了解 | 0.29**(0.098) | 相关了解 | 0.29**(0.098) |
机器人使用a | 1.35***(0.167) | 机器人使用a | 1.40***(0.167) |
机器人使用c | 0.28(0.338) | 机器人使用c | 0.31(0.338) |
社会阶层 | −0.01(0.050) | 社会阶层 | 0.00(0.050) |
Gini系数 | 0.06***(0.013) | Gini系数 | 0.06***(0.013) |
ln GDP | 15.03***(0.081) | ln GDP | 15.07***(0.080) |
机器人威胁指标1 | −0.51***(0.059) | 机器人威胁指标2 | −0.60***(0.102) |
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | ||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 性别 | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 年龄 | 0.01 | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 社区 | 0.00 | −0.024** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 教育 | −0.035*** | 0.02 | 0.124*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||
5 | 政治取向 | 0.050*** | 0.01 | 0.01 | −0.037*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||
6 | 技术技能a | 0.01 | −0.219*** | 0.062*** | 0.239*** | 0.00 | — | ||||||||||||||||||||||||||||||||||||||||||||||||
7 | 技术技能b | 0.00 | −0.181*** | 0.072*** | 0.277*** | −0.01 | 0.762*** | — | |||||||||||||||||||||||||||||||||||||||||||||||
8 | 技术技能c | 0.01 | −0.261*** | 0.083*** | 0.248*** | −0.01 | 0.715*** | 0.724*** | — | ||||||||||||||||||||||||||||||||||||||||||||||
9 | 工作被 替代 | 0.059*** | −0.077*** | 0.044*** | −0.051*** | 0.024* | 0.01 | 0.00 | 0.026** | — | |||||||||||||||||||||||||||||||||||||||||||||
10 | 相关了解 | −0.088*** | 0.01 | −0.055*** | −0.247*** | 0.039*** | −0.276*** | −0.290*** | −0.264*** | −0.030** | — | ||||||||||||||||||||||||||||||||||||||||||||
11 | 机器人 使用a | 0.00 | 0.02 | −0.01 | −0.077*** | −0.025** | −0.084*** | −0.089*** | −0.088*** | −0.085*** | 0.104*** | — | |||||||||||||||||||||||||||||||||||||||||||
12 | 机器人 使用b | −0.097*** | 0.032*** | 0.00 | −0.036*** | −0.02 | −0.058*** | −0.079*** | −0.078*** | −0.133*** | 0.118*** | 0.156*** | — | ||||||||||||||||||||||||||||||||||||||||||
13 | 机器人 使用c | −0.027** | 0.032*** | −0.034*** | −0.022* | 0.01 | −0.01 | −0.018* | −0.025*** | −0.061*** | 0.037*** | 0.043*** | 0.067*** | — | |||||||||||||||||||||||||||||||||||||||||
14 | 社会阶层 | −0.023** | 0.02 | 0.121*** | 0.315*** | 0.048*** | 0.204*** | 0.240*** | 0.224*** | −0.061*** | −0.188*** | −0.105*** | −0.047*** | −0.036*** | — | ||||||||||||||||||||||||||||||||||||||||
15 | Gini系数 | 0.01 | −0.032*** | 0.084*** | −0.125*** | 0.024* | −0.035*** | −0.065*** | −0.040*** | 0.067*** | 0.142*** | 0.074*** | 0.078*** | 0.017* | −0.184*** | — | |||||||||||||||||||||||||||||||||||||||
16 | ln GDP | 0.046*** | 0.075*** | −0.048*** | 0.165*** | −0.139*** | 0.161*** | 0.180*** | 0.169*** | −0.101*** | −0.222*** | −0.063*** | −0.068*** | −0.022* | 0.175*** | −0.349*** | — | ||||||||||||||||||||||||||||||||||||||
17 | 机器人 威胁a | −0.057*** | −0.01 | −0.052*** | −0.133*** | −0.020* | −0.074*** | −0.096*** | −0.089*** | 0.036*** | 0.108*** | 0.051*** | 0.056*** | 0.027** | −0.142*** | 0.154*** | −0.098*** | — | |||||||||||||||||||||||||||||||||||||
18 | 机器人 威胁b | −0.032*** | 0.01 | −0.028** | −0.101*** | −0.020* | −0.205*** | −0.203*** | −0.195*** | −0.123*** | 0.127*** | 0.116*** | 0.073*** | 0.02 | −0.074*** | −0.018* | 0.052*** | 0.094*** | — | ||||||||||||||||||||||||||||||||||||
19 | 机器人 威胁c | 0.00 | 0.051*** | 0.00 | 0.072*** | −0.01 | 0.149*** | 0.132*** | 0.101*** | −0.033*** | −0.159*** | 0.01 | 0.01 | 0.036*** | −0.01 | 0.036*** | 0.077*** | 0.199*** | −0.204*** | — | |||||||||||||||||||||||||||||||||||
20 | 机器人 威胁d | −0.033*** | −0.034*** | −0.022* | −0.094*** | −0.020* | −0.198*** | −0.192*** | −0.160*** | −0.052*** | 0.169*** | 0.065*** | 0.051*** | −0.01 | −0.038*** | −0.024** | 0.00 | −0.02 | 0.458*** | −0.365*** | — | ||||||||||||||||||||||||||||||||||
21 | 机器人 威胁e | −0.048*** | 0.00 | −0.065*** | −0.191*** | 0.00 | −0.124*** | −0.157*** | −0.136*** | 0.045*** | 0.165*** | 0.049*** | 0.068*** | 0.01 | −0.192*** | 0.187*** | −0.141*** | 0.626*** | 0.140*** | 0.135*** | 0.042*** | — | |||||||||||||||||||||||||||||||||
22 | 机器人威胁指标 | −0.056*** | −0.01 | −0.063*** | −0.178*** | −0.01 | −0.112*** | −0.141*** | −0.125*** | 0.046*** | 0.150*** | 0.053*** | 0.067*** | 0.018* | −0.185*** | 0.189*** | −0.132*** | 0.898*** | 0.129*** | 0.180*** | 0.01 | 0.909*** | — | ||||||||||||||||||||||||||||||||
23 | 机器人威胁指标 | −0.064*** | 0.00 | −0.064*** | −0.176*** | −0.023* | −0.181*** | −0.203*** | −0.187*** | −0.041*** | 0.166*** | 0.106*** | 0.094*** | 0.027** | −0.174*** | 0.132*** | −0.049*** | 0.723*** | 0.562*** | 0.231*** | 0.415*** | 0.748*** | 0.810*** | — | |||||||||||||||||||||||||||||||
24 | 帮助他人 | 0.076*** | 0.032*** | −0.025** | 0.106*** | −0.119*** | 0.099*** | 0.108*** | 0.118*** | −0.043*** | −0.090*** | 0.00 | −0.023** | −0.020* | 0.049*** | 0.041*** | 0.580*** | −0.049*** | 0.036*** | 0.060*** | 0.019* | −0.078*** | −0.069*** | −0.01 | — | ||||||||||||||||||||||||||||||
25 | 金钱捐赠 | 0.048*** | 0.055*** | −0.050*** | 0.149*** | −0.122*** | 0.166*** | 0.198*** | 0.192*** | −0.093*** | −0.177*** | −0.026** | −0.041*** | 0.00 | 0.157*** | −0.315*** | 0.775*** | −0.126*** | 0.019* | 0.061*** | 0.00 | −0.185*** | −0.172*** | −0.096*** | 0.632*** | — | |||||||||||||||||||||||||||||
26 | 时间付出 | 0.019* | 0.033*** | −0.079*** | 0.066*** | −0.115*** | 0.112*** | 0.136*** | 0.135*** | −0.090*** | −0.150*** | −0.022** | −0.047*** | −0.01 | 0.112*** | −0.429*** | 0.766*** | −0.066*** | 0.081*** | 0.036*** | 0.038*** | −0.109*** | −0.098*** | −0.02 | 0.486*** | 0.698*** | — | ||||||||||||||||||||||||||||
27 | 捐赠指数 | 0.057*** | 0.051*** | −0.056*** | 0.134*** | −0.135*** | 0.154*** | 0.180*** | 0.179*** | −0.089*** | −0.167*** | −0.019* | −0.041*** | −0.01 | 0.130*** | −0.256*** | 0.818*** | −0.101*** | 0.043*** | 0.066*** | 0.01 | −0.154*** | −0.141*** | −0.057*** | 0.820*** | 0.936*** | 0.805*** | — | |||||||||||||||||||||||||||
M | 44.06 | 1.98 | 20.55 | 5.38 | 3.23 | 3.18 | 3.03 | 1.71 | 0.47 | 0.91 | 0.92 | 0.98 | 2.47 | 31.57 | 10.13 | 3.11 | 2.04 | 3.50 | 1.67 | 3.02 | 3.06 | 2.67 | 44.10 | 34.73 | 19.37 | 32.79 | |||||||||||||||||||||||||||||
SD | 12.20 | 0.79 | 4.75 | 2.15 | 0.85 | 0.92 | 0.93 | 0.88 | 0.50 | 0.29 | 0.27 | 0.14 | 0.97 | 3.86 | 0.62 | 0.85 | 0.81 | 0.65 | 0.75 | 0.89 | 0.79 | 0.45 | 11.71 | 17.42 | 9.35 | 11.13 |
表6 劳动力样本: 相关性与描述性数据
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | ||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 性别 | — | |||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 年龄 | 0.01 | — | ||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 社区 | 0.00 | −0.024** | — | |||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 教育 | −0.035*** | 0.02 | 0.124*** | — | ||||||||||||||||||||||||||||||||||||||||||||||||||
5 | 政治取向 | 0.050*** | 0.01 | 0.01 | −0.037*** | — | |||||||||||||||||||||||||||||||||||||||||||||||||
6 | 技术技能a | 0.01 | −0.219*** | 0.062*** | 0.239*** | 0.00 | — | ||||||||||||||||||||||||||||||||||||||||||||||||
7 | 技术技能b | 0.00 | −0.181*** | 0.072*** | 0.277*** | −0.01 | 0.762*** | — | |||||||||||||||||||||||||||||||||||||||||||||||
8 | 技术技能c | 0.01 | −0.261*** | 0.083*** | 0.248*** | −0.01 | 0.715*** | 0.724*** | — | ||||||||||||||||||||||||||||||||||||||||||||||
9 | 工作被 替代 | 0.059*** | −0.077*** | 0.044*** | −0.051*** | 0.024* | 0.01 | 0.00 | 0.026** | — | |||||||||||||||||||||||||||||||||||||||||||||
10 | 相关了解 | −0.088*** | 0.01 | −0.055*** | −0.247*** | 0.039*** | −0.276*** | −0.290*** | −0.264*** | −0.030** | — | ||||||||||||||||||||||||||||||||||||||||||||
11 | 机器人 使用a | 0.00 | 0.02 | −0.01 | −0.077*** | −0.025** | −0.084*** | −0.089*** | −0.088*** | −0.085*** | 0.104*** | — | |||||||||||||||||||||||||||||||||||||||||||
12 | 机器人 使用b | −0.097*** | 0.032*** | 0.00 | −0.036*** | −0.02 | −0.058*** | −0.079*** | −0.078*** | −0.133*** | 0.118*** | 0.156*** | — | ||||||||||||||||||||||||||||||||||||||||||
13 | 机器人 使用c | −0.027** | 0.032*** | −0.034*** | −0.022* | 0.01 | −0.01 | −0.018* | −0.025*** | −0.061*** | 0.037*** | 0.043*** | 0.067*** | — | |||||||||||||||||||||||||||||||||||||||||
14 | 社会阶层 | −0.023** | 0.02 | 0.121*** | 0.315*** | 0.048*** | 0.204*** | 0.240*** | 0.224*** | −0.061*** | −0.188*** | −0.105*** | −0.047*** | −0.036*** | — | ||||||||||||||||||||||||||||||||||||||||
15 | Gini系数 | 0.01 | −0.032*** | 0.084*** | −0.125*** | 0.024* | −0.035*** | −0.065*** | −0.040*** | 0.067*** | 0.142*** | 0.074*** | 0.078*** | 0.017* | −0.184*** | — | |||||||||||||||||||||||||||||||||||||||
16 | ln GDP | 0.046*** | 0.075*** | −0.048*** | 0.165*** | −0.139*** | 0.161*** | 0.180*** | 0.169*** | −0.101*** | −0.222*** | −0.063*** | −0.068*** | −0.022* | 0.175*** | −0.349*** | — | ||||||||||||||||||||||||||||||||||||||
17 | 机器人 威胁a | −0.057*** | −0.01 | −0.052*** | −0.133*** | −0.020* | −0.074*** | −0.096*** | −0.089*** | 0.036*** | 0.108*** | 0.051*** | 0.056*** | 0.027** | −0.142*** | 0.154*** | −0.098*** | — | |||||||||||||||||||||||||||||||||||||
18 | 机器人 威胁b | −0.032*** | 0.01 | −0.028** | −0.101*** | −0.020* | −0.205*** | −0.203*** | −0.195*** | −0.123*** | 0.127*** | 0.116*** | 0.073*** | 0.02 | −0.074*** | −0.018* | 0.052*** | 0.094*** | — | ||||||||||||||||||||||||||||||||||||
19 | 机器人 威胁c | 0.00 | 0.051*** | 0.00 | 0.072*** | −0.01 | 0.149*** | 0.132*** | 0.101*** | −0.033*** | −0.159*** | 0.01 | 0.01 | 0.036*** | −0.01 | 0.036*** | 0.077*** | 0.199*** | −0.204*** | — | |||||||||||||||||||||||||||||||||||
20 | 机器人 威胁d | −0.033*** | −0.034*** | −0.022* | −0.094*** | −0.020* | −0.198*** | −0.192*** | −0.160*** | −0.052*** | 0.169*** | 0.065*** | 0.051*** | −0.01 | −0.038*** | −0.024** | 0.00 | −0.02 | 0.458*** | −0.365*** | — | ||||||||||||||||||||||||||||||||||
21 | 机器人 威胁e | −0.048*** | 0.00 | −0.065*** | −0.191*** | 0.00 | −0.124*** | −0.157*** | −0.136*** | 0.045*** | 0.165*** | 0.049*** | 0.068*** | 0.01 | −0.192*** | 0.187*** | −0.141*** | 0.626*** | 0.140*** | 0.135*** | 0.042*** | — | |||||||||||||||||||||||||||||||||
22 | 机器人威胁指标 | −0.056*** | −0.01 | −0.063*** | −0.178*** | −0.01 | −0.112*** | −0.141*** | −0.125*** | 0.046*** | 0.150*** | 0.053*** | 0.067*** | 0.018* | −0.185*** | 0.189*** | −0.132*** | 0.898*** | 0.129*** | 0.180*** | 0.01 | 0.909*** | — | ||||||||||||||||||||||||||||||||
23 | 机器人威胁指标 | −0.064*** | 0.00 | −0.064*** | −0.176*** | −0.023* | −0.181*** | −0.203*** | −0.187*** | −0.041*** | 0.166*** | 0.106*** | 0.094*** | 0.027** | −0.174*** | 0.132*** | −0.049*** | 0.723*** | 0.562*** | 0.231*** | 0.415*** | 0.748*** | 0.810*** | — | |||||||||||||||||||||||||||||||
24 | 帮助他人 | 0.076*** | 0.032*** | −0.025** | 0.106*** | −0.119*** | 0.099*** | 0.108*** | 0.118*** | −0.043*** | −0.090*** | 0.00 | −0.023** | −0.020* | 0.049*** | 0.041*** | 0.580*** | −0.049*** | 0.036*** | 0.060*** | 0.019* | −0.078*** | −0.069*** | −0.01 | — | ||||||||||||||||||||||||||||||
25 | 金钱捐赠 | 0.048*** | 0.055*** | −0.050*** | 0.149*** | −0.122*** | 0.166*** | 0.198*** | 0.192*** | −0.093*** | −0.177*** | −0.026** | −0.041*** | 0.00 | 0.157*** | −0.315*** | 0.775*** | −0.126*** | 0.019* | 0.061*** | 0.00 | −0.185*** | −0.172*** | −0.096*** | 0.632*** | — | |||||||||||||||||||||||||||||
26 | 时间付出 | 0.019* | 0.033*** | −0.079*** | 0.066*** | −0.115*** | 0.112*** | 0.136*** | 0.135*** | −0.090*** | −0.150*** | −0.022** | −0.047*** | −0.01 | 0.112*** | −0.429*** | 0.766*** | −0.066*** | 0.081*** | 0.036*** | 0.038*** | −0.109*** | −0.098*** | −0.02 | 0.486*** | 0.698*** | — | ||||||||||||||||||||||||||||
27 | 捐赠指数 | 0.057*** | 0.051*** | −0.056*** | 0.134*** | −0.135*** | 0.154*** | 0.180*** | 0.179*** | −0.089*** | −0.167*** | −0.019* | −0.041*** | −0.01 | 0.130*** | −0.256*** | 0.818*** | −0.101*** | 0.043*** | 0.066*** | 0.01 | −0.154*** | −0.141*** | −0.057*** | 0.820*** | 0.936*** | 0.805*** | — | |||||||||||||||||||||||||||
M | 44.06 | 1.98 | 20.55 | 5.38 | 3.23 | 3.18 | 3.03 | 1.71 | 0.47 | 0.91 | 0.92 | 0.98 | 2.47 | 31.57 | 10.13 | 3.11 | 2.04 | 3.50 | 1.67 | 3.02 | 3.06 | 2.67 | 44.10 | 34.73 | 19.37 | 32.79 | |||||||||||||||||||||||||||||
SD | 12.20 | 0.79 | 4.75 | 2.15 | 0.85 | 0.92 | 0.93 | 0.88 | 0.50 | 0.29 | 0.27 | 0.14 | 0.97 | 3.86 | 0.62 | 0.85 | 0.81 | 0.65 | 0.75 | 0.89 | 0.79 | 0.45 | 11.71 | 17.42 | 9.35 | 11.13 |
变量 | 回归系数与显著性 | 变量 | 回归系数与显著性 |
---|---|---|---|
(常量) | −125.47(1.636) | (常量) | −125.90(1.654) |
性别 | 0.38**(0.130) | 性别 | 0.39**(0.130) |
年龄 | 0.01(0.006) | 年龄 | 0.01(0.006) |
社区 | −0.28**(0.083) | 社区 | −0.27**(0.083) |
教育 | −0.02(0.014) | 教育 | −0.01(0.014) |
政治取向 | −0.15***(0.030) | 政治取向 | −0.15***(0.030) |
技术技能a | −0.40**(0.127) | 技术技能a | −0.42**(0.127) |
技术技能b | 0.54***(0.120) | 技术技能b | 0.54***(0.120) |
技术技能c | 0.58***(0.108) | 技术技能c | 0.58***(0.108) |
工作被替代 | −0.13(0.075) | 工作被替代 | −0.17*(0.075) |
相关了解 | 0.31*(0.141) | 相关了解 | 0.29*(0.141) |
机器人使用a | 1.03***(0.223) | 机器人使用a | 1.08***(0.223) |
机器人使用b | 0.48*(0.232) | 机器人使用b | 0.46*(0.232) |
机器人使用c | 0.26(0.456) | 机器人使用c | 0.27(0.457) |
社会阶层 | −0.22**(0.073) | 社会阶层 | −0.19**(0.073) |
Gini系数 | 0.13***(0.019) | Gini系数 | 0.13***(0.018) |
ln GDP | 15.19***(0.116) | ln GDP | 15.23***(0.116) |
机器人威胁指标1 | −0.60***(0.085) | 机器人威胁指标2 | −0.63***(0.152) |
表7 劳动力样本中的机器人威胁与亲社会行为
变量 | 回归系数与显著性 | 变量 | 回归系数与显著性 |
---|---|---|---|
(常量) | −125.47(1.636) | (常量) | −125.90(1.654) |
性别 | 0.38**(0.130) | 性别 | 0.39**(0.130) |
年龄 | 0.01(0.006) | 年龄 | 0.01(0.006) |
社区 | −0.28**(0.083) | 社区 | −0.27**(0.083) |
教育 | −0.02(0.014) | 教育 | −0.01(0.014) |
政治取向 | −0.15***(0.030) | 政治取向 | −0.15***(0.030) |
技术技能a | −0.40**(0.127) | 技术技能a | −0.42**(0.127) |
技术技能b | 0.54***(0.120) | 技术技能b | 0.54***(0.120) |
技术技能c | 0.58***(0.108) | 技术技能c | 0.58***(0.108) |
工作被替代 | −0.13(0.075) | 工作被替代 | −0.17*(0.075) |
相关了解 | 0.31*(0.141) | 相关了解 | 0.29*(0.141) |
机器人使用a | 1.03***(0.223) | 机器人使用a | 1.08***(0.223) |
机器人使用b | 0.48*(0.232) | 机器人使用b | 0.46*(0.232) |
机器人使用c | 0.26(0.456) | 机器人使用c | 0.27(0.457) |
社会阶层 | −0.22**(0.073) | 社会阶层 | −0.19**(0.073) |
Gini系数 | 0.13***(0.019) | Gini系数 | 0.13***(0.018) |
ln GDP | 15.19***(0.116) | ln GDP | 15.23***(0.116) |
机器人威胁指标1 | −0.60***(0.085) | 机器人威胁指标2 | −0.63***(0.152) |
国家 | 样本量(N) | 性别 (女性占比) | 年龄(M/SD) | ln (GDP) (10亿) | |
---|---|---|---|---|---|
1 | 法国 | 1059 | 55.15% | 49.97 (19.19) | 3.46 |
2 | 比利时 | 1051 | 53.00% | 49.81 (17.80) | 2.72 |
3 | 荷兰 | 1014 | 52.86% | 50.68 (18.61) | 2.96 |
4 | 德国 | 1552 | 49.74% | 52.44 (18.22) | 3.57 |
5 | 意大利 | 1036 | 56.56% | 47.44 (16.82) | 3.36 |
6 | 卢森堡 | 501 | 54.69% | 47.81 (17.87) | 1.79 |
7 | 丹麦 | 1019 | 50.34% | 50.84 (18.26) | 2.54 |
8 | 爱尔兰 | 1008 | 54.27% | 45.64 (17.14) | 2.38 |
9 | 英国 | 1331 | 53.57% | 50.74 (20.21) | 3.42 |
10 | 希腊 | 999 | 53.25% | 46.08 (17.36) | 2.45 |
11 | 西班牙 | 1004 | 53.09% | 47.18 (18.87) | 3.17 |
12 | 葡萄牙 | 1009 | 54.51% | 48.90 (18.74) | 2.39 |
13 | 芬兰 | 1003 | 53.64% | 55.58 (18.60) | 2.44 |
14 | 瑞典 | 1016 | 48.33% | 57.51 (15.78) | 2.76 |
15 | 奥地利 | 1031 | 56.06% | 46.01 (15.94) | 2.64 |
16 | 塞浦路斯 | 506 | 50.99% | 43.38 (17.29) | 1.44 |
17 | 捷克共和国 | 1003 | 56.73% | 46.12 (16.40) | 2.36 |
18 | 爱沙尼亚 | 1000 | 62.60% | 49.84 (19.26) | 1.37 |
19 | 匈牙利 | 1021 | 56.90% | 47.83 (17.37) | 2.15 |
20 | 拉脱维亚 | 1024 | 53.52% | 42.76 (16.86) | 1.44 |
21 | 立陶宛 | 1021 | 54.95% | 46.32 (18.12) | 1.64 |
22 | 马耳他 | 500 | 62.00% | 51.63 (17.88) | 0.98 |
23 | 波兰 | 1000 | 58.90% | 49.26 (18.85) | 2.72 |
24 | 斯洛伐克 | 1000 | 58.20% | 45.96 (15.32) | 2.00 |
25 | 斯洛文尼亚 | 1017 | 52.02% | 48.33 (17.90) | 1.71 |
26 | 保加利亚 | 1006 | 51.99% | 48.16 (16.82) | 1.76 |
27 | 罗马利亚 | 1020 | 47.65% | 44.98 (16.61) | 2.28 |
总计 | 26, 751 | 54.08% | 48.72 (18.08) |
表8 各国家的人口统计学信息和经济水平
国家 | 样本量(N) | 性别 (女性占比) | 年龄(M/SD) | ln (GDP) (10亿) | |
---|---|---|---|---|---|
1 | 法国 | 1059 | 55.15% | 49.97 (19.19) | 3.46 |
2 | 比利时 | 1051 | 53.00% | 49.81 (17.80) | 2.72 |
3 | 荷兰 | 1014 | 52.86% | 50.68 (18.61) | 2.96 |
4 | 德国 | 1552 | 49.74% | 52.44 (18.22) | 3.57 |
5 | 意大利 | 1036 | 56.56% | 47.44 (16.82) | 3.36 |
6 | 卢森堡 | 501 | 54.69% | 47.81 (17.87) | 1.79 |
7 | 丹麦 | 1019 | 50.34% | 50.84 (18.26) | 2.54 |
8 | 爱尔兰 | 1008 | 54.27% | 45.64 (17.14) | 2.38 |
9 | 英国 | 1331 | 53.57% | 50.74 (20.21) | 3.42 |
10 | 希腊 | 999 | 53.25% | 46.08 (17.36) | 2.45 |
11 | 西班牙 | 1004 | 53.09% | 47.18 (18.87) | 3.17 |
12 | 葡萄牙 | 1009 | 54.51% | 48.90 (18.74) | 2.39 |
13 | 芬兰 | 1003 | 53.64% | 55.58 (18.60) | 2.44 |
14 | 瑞典 | 1016 | 48.33% | 57.51 (15.78) | 2.76 |
15 | 奥地利 | 1031 | 56.06% | 46.01 (15.94) | 2.64 |
16 | 塞浦路斯 | 506 | 50.99% | 43.38 (17.29) | 1.44 |
17 | 捷克共和国 | 1003 | 56.73% | 46.12 (16.40) | 2.36 |
18 | 爱沙尼亚 | 1000 | 62.60% | 49.84 (19.26) | 1.37 |
19 | 匈牙利 | 1021 | 56.90% | 47.83 (17.37) | 2.15 |
20 | 拉脱维亚 | 1024 | 53.52% | 42.76 (16.86) | 1.44 |
21 | 立陶宛 | 1021 | 54.95% | 46.32 (18.12) | 1.64 |
22 | 马耳他 | 500 | 62.00% | 51.63 (17.88) | 0.98 |
23 | 波兰 | 1000 | 58.90% | 49.26 (18.85) | 2.72 |
24 | 斯洛伐克 | 1000 | 58.20% | 45.96 (15.32) | 2.00 |
25 | 斯洛文尼亚 | 1017 | 52.02% | 48.33 (17.90) | 1.71 |
26 | 保加利亚 | 1006 | 51.99% | 48.16 (16.82) | 1.76 |
27 | 罗马利亚 | 1020 | 47.65% | 44.98 (16.61) | 2.28 |
总计 | 26, 751 | 54.08% | 48.72 (18.08) |
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 性别 | — | ||||||||||||
2 | 年龄 | 0.02*** | — | |||||||||||
3 | 社区 | 0.01 | −0.05*** | — | ||||||||||
4 | 教育 | −0.01* | −0.13*** | 0.13*** | — | |||||||||
5 | 社会阶层 | −0.02*** | −0.07*** | 0.04*** | 0.23*** | — | ||||||||
6 | 科学兴趣 | −0.02*** | −0.15*** | 0.08*** | 0.27*** | 0.19*** | — | |||||||
7 | 机器人使用a | 0.01 | −0.05*** | 0.01 | 0.03*** | 0.04*** | 0.06*** | — | ||||||
8 | 机器人使用b | −0.12*** | −0.06*** | −0.02** | 0.06*** | 0.04*** | 0.12*** | 0.09*** | — | |||||
9 | 机器人使用c | −0.02*** | −0.04*** | −0.02** | 0.01* | 0.02** | 0.04*** | 0.02*** | 0.00 | — | ||||
10 | 机器人 一般态度 | −0.13*** | −0.12*** | 0.05*** | 0.2*** | 0.13*** | 0.40*** | 0.12*** | 0.13*** | 0.05*** | — | |||
11 | ln GDP | −0.02*** | 0.07 | 0.01 | −0.01* | 0.10*** | 0.07*** | 0.02*** | 0.04*** | −0.00 | −0.01 | — | ||
12 | 机器人威胁 | −0.10** | 0.06*** | −0.04*** | −0.20*** | −0.14*** | −0.26*** | −0.08*** | −0.10*** | −0.04*** | −0.55*** | 0.01 | — | |
13 | 亲社会倾向 | −0.00 | −0.05*** | 0.06*** | 0.15*** | −0.11*** | 0.22*** | 0.03*** | 0.02** | 0.00 | −0.2*** | −0.02** | −0.15*** | — |
M | 48.72 | 1.92 | 19.02 | 5.54 | 2.01 | 0.05 | 0.06 | 0.01 | 2.87 | 2.46 | 2.52 | 2.99 | ||
SD | 18.08 | 0.80 | 4.74 | 1.63 | 0.68 | 0.21 | 0.23 | 0.11 | 0.74 | 0.68 | 0.48 | 0.51 |
表9 相关性与描述性数据
变量 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 性别 | — | ||||||||||||
2 | 年龄 | 0.02*** | — | |||||||||||
3 | 社区 | 0.01 | −0.05*** | — | ||||||||||
4 | 教育 | −0.01* | −0.13*** | 0.13*** | — | |||||||||
5 | 社会阶层 | −0.02*** | −0.07*** | 0.04*** | 0.23*** | — | ||||||||
6 | 科学兴趣 | −0.02*** | −0.15*** | 0.08*** | 0.27*** | 0.19*** | — | |||||||
7 | 机器人使用a | 0.01 | −0.05*** | 0.01 | 0.03*** | 0.04*** | 0.06*** | — | ||||||
8 | 机器人使用b | −0.12*** | −0.06*** | −0.02** | 0.06*** | 0.04*** | 0.12*** | 0.09*** | — | |||||
9 | 机器人使用c | −0.02*** | −0.04*** | −0.02** | 0.01* | 0.02** | 0.04*** | 0.02*** | 0.00 | — | ||||
10 | 机器人 一般态度 | −0.13*** | −0.12*** | 0.05*** | 0.2*** | 0.13*** | 0.40*** | 0.12*** | 0.13*** | 0.05*** | — | |||
11 | ln GDP | −0.02*** | 0.07 | 0.01 | −0.01* | 0.10*** | 0.07*** | 0.02*** | 0.04*** | −0.00 | −0.01 | — | ||
12 | 机器人威胁 | −0.10** | 0.06*** | −0.04*** | −0.20*** | −0.14*** | −0.26*** | −0.08*** | −0.10*** | −0.04*** | −0.55*** | 0.01 | — | |
13 | 亲社会倾向 | −0.00 | −0.05*** | 0.06*** | 0.15*** | −0.11*** | 0.22*** | 0.03*** | 0.02** | 0.00 | −0.2*** | −0.02** | −0.15*** | — |
M | 48.72 | 1.92 | 19.02 | 5.54 | 2.01 | 0.05 | 0.06 | 0.01 | 2.87 | 2.46 | 2.52 | 2.99 | ||
SD | 18.08 | 0.80 | 4.74 | 1.63 | 0.68 | 0.21 | 0.23 | 0.11 | 0.74 | 0.68 | 0.48 | 0.51 |
变量 | 亲社会倾向 |
---|---|
回归系数与显著性 | |
感知机器人威胁 | −0.077*** (0.007) |
对机器人的一般态度 | 0.069*** (0.005) |
机器人使用: 在家 | 0.024 (0.014) |
机器人使用: 工作上 | −0.026 (0.013) |
机器人使用: 其他地方 | −0.024 (0.027) |
科学兴趣 | 控制 |
社会阶层 | 控制 |
教育 | 0.002***(0.0003) |
社区 | 控制 |
年龄 | −0.000** (0.0002) |
性别 | 0.052*** (0.006) |
常量 | 2.614*** (0.043) |
国家固定效应 | 控制 |
观测值 | 25769 |
调整R | 0.113 |
F | 99.74*** |
表10 感知机器人威胁和亲社会倾向
变量 | 亲社会倾向 |
---|---|
回归系数与显著性 | |
感知机器人威胁 | −0.077*** (0.007) |
对机器人的一般态度 | 0.069*** (0.005) |
机器人使用: 在家 | 0.024 (0.014) |
机器人使用: 工作上 | −0.026 (0.013) |
机器人使用: 其他地方 | −0.024 (0.027) |
科学兴趣 | 控制 |
社会阶层 | 控制 |
教育 | 0.002***(0.0003) |
社区 | 控制 |
年龄 | −0.000** (0.0002) |
性别 | 0.052*** (0.006) |
常量 | 2.614*** (0.043) |
国家固定效应 | 控制 |
观测值 | 25769 |
调整R | 0.113 |
F | 99.74*** |
[1] |
Adler, N. E., Epel, E. S., Castellazzo, G., & Ickovics, J. R. (2000). Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy white women. Health Psychology, 19(6), 586-592.
doi: 10.1037//0278-6133.19.6.586 pmid: 11129362 |
[2] | Agarwat, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694. |
[3] | Agrawal, A., Gans, J., & Goldfarb, A. (2019). The economics of artificial intelligence: An agenda. Chicago and London: The University of Chicago Press. |
[4] | Andrighetto, L., Vezzali, L., Bergamini, G., Nadi, C., & Giovannini, D. (2016). Inside the earthquake: Perceived disaster exposure and helping intentions among Italian and immigrant victims of the 2012 Italian earthquakes. Group Processes and Intergroup Relations, 19(6), 753-768. |
[5] | Aron, A., Aron, E. N., & Smollan, D. (1992). Inclusion of Other in the Self Scale and the structure of interpersonal closeness. Journal of Personality and Social Psychology, 63(4), 596-612. |
[6] | Asimov, I. (1950). I, Robot. New York: Gnome Press. |
[7] | Bai, M., Zhang, H., Zhang, J., Jiang, Y., & Xu, J. (2025). Challenging or threatening? The double-edged sword effect of intelligent technology awareness on accountants’ unethical decision-making. Journal of Business Ethics, 197, 159-175. |
[8] | Barnes, C. M., Dang, C. T., Leavitt, K., Guarana, C. L., & Uhlmann, E. L. (2018). Archival data in micro- organizational research: A toolkit for moving to a broader set of topics. Journal of Management, 44(4), 1453-1478. |
[9] | Batson, C. D., & Powell, A. A. (2003). Altruism and prosocial behavior. In T. Millon & M. J. Lerner (Eds.), Handbook of psychology: Personality and social psychology (Vol. 5, pp. 463-484) Hoboken, NJ: Wiley. |
[10] |
Bavel, J. J. V., Baicker, K., Boggio, P. S., Capraro, V., Cichocka, A., Cikara, M.,... Willer, R. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour, 4(5), 460-471.
doi: 10.1038/s41562-020-0884-z pmid: 32355299 |
[11] | Bobo, L. (1983). Whites' opposition to busing: Symbolic racism or realistic group conflict? Journal of Personality and Social Psychology, 45(6), 1196-1210. |
[12] | Bordot, F. (2022). Artificial intelligence, robots and unemployment: Evidence from OECD countries. Journal of Innovation Economics and Management, 37(1), 117-138. |
[13] | Bostrom, N. (2002). Existential risks: Analyzing human extinction scenarios and related hazards. Journal of Evolution and Technology, 9, 1-30. |
[14] | Brewer, M. B. (1999). The psychology of prejudice: Ingroup love or outgroup hate?. Journal of Social Issues, 55(3), 429-444. |
[15] | Brewer, M. B. (2001). The many faces of social identity: Implications for political psychology. Political Psychology, 22(1), 115-125. |
[16] | Butz, D. A., & Yogeeswaran, K. (2011). A new threat in the air: Macroeconomic threat increases prejudice against Asian Americans. Journal of Experimental Social Psychology, 47(1), 22-27. |
[17] | Carradore, M. (2022). People’s attitudes towards the use of robots in the social services: A multilevel analysis using eurobarometer data. International Journal of Social Robotics, 14, 845-858. |
[18] |
Cortland, C. I., Craig, M. A., Shapiro, J. R., Richeson, J. A., Neel, R., & Goldstein, N. J. (2017). Solidarity through shared disadvantage: Highlighting shared experiences of discrimination improves relations between stigmatized groups. Journal of Personality and Social Psychology, 113(4), 547-567.
doi: 10.1037/pspi0000100 pmid: 28581301 |
[19] |
Diel, K., Grelle, S., & Hofmann, W. (2021). A motivational framework of social comparison. Journal of Personality and Social Psychology, 120(6), 1415-1430.
doi: 10.1037/pspa0000204 pmid: 33507785 |
[20] | Diel, K., & Hofmann, W. (2019). Inspired to perspire: The interplay of social comparison direction and standard extremity in the context of challenging exercising goals. Social Cognition, 37(3), 247-265 |
[21] |
Dovidio, J. F., ten Vergert, M., Stewart, T. L., Gaertner, S. L., Johnson, J. D., Esses, V. M., Riek, B. M., & Pearson, A. R. (2004). Perspective and prejudice: Antecedents and mediating mechanisms. Personality and Social Psychology Bulletin, 30(12), 1537-1549.
doi: 10.1177/0146167204271177 pmid: 15536238 |
[22] | Drury, J. (2018). The role of social identity processes in mass emergency behaviour: An integrative review. European Review of Social Psychology, 29(1), 38-81. |
[23] |
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191.
doi: 10.3758/bf03193146 pmid: 17695343 |
[24] |
Fleischmann, A., Lammers, J., Diel, K., Hofmann, W., & Galinsky, A. D. (2021). More threatening and more diagnostic: How moral comparisons differ from social comparisons. Journal of Personality and Social Psychology, 121(5), 1057-1078.
doi: 10.1037/pspi0000361 pmid: 33646800 |
[94] | World, Bank. (2016). World Bank national accounts data, and OECD National Accounts data files. Retrieved August 27, 2024, from https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?end=2016&start=2016 |
[95] | Wu, N. (2022a). Misattributed blame? Attitudes toward globalization in the age of automation. Political Science Research and Methods, 10(3), 470-487. |
[96] | Wu, N. (2022b). “Restrict foreigners, not robots”: Partisan responses to automation threat. Economics & Politics, 35(2), 1-24. |
[97] | Wu, T. J., Liang, Y., & Wang, Y. (2024). The buffering role of workplace mindfulness: How job insecurity of human- artificial intelligence collaboration impacts employees’ work-life-related outcomes. Journal of Business and Psychology, 39, 1395-1411. |
[98] |
Xu, L., Wang, X., Yu, F., & Peng, K. (2024). The influence of perceived robot threat on workplace objectification. Acta Psychologica Sinica, 56(2), 210-225.
doi: 10.3724/SP.J.1041.2024.00210 |
[许丽颖, 王学辉, 喻丰, 彭凯平. (2024). 感知机器人威胁对职场物化的影响. 心理学报, 56(2), 210-225.]
doi: 10.3724/SP.J.1041.2024.00210 |
|
[99] | Yang, Y., Sedikides, C., Wang, Y., & Cai, H. (2024). Nature nurtures authenticity: Mechanisms and consequences. Journal of Personality and Social Psychology, 126(1), 79-104. |
[100] | Yam, K. C., Tang, P. M., Jackson, J. C., Su, R., & Gray, K. (2023). The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence. Journal of Applied Psychology, 108(5), 850-870. |
[101] | Yogeeswaran, K., Złotowski, J., Livingstone, M., Bartneck, C., Sumioka, H., & Ishiguro, H. (2016). The interactive effects of robot anthropomorphism and robot ability on perceived threat and support for robotics research. Journal of Human-Robot Interaction, 5(2), 29-47. |
[102] | Yudkowsky, E. (2008). Artificial intelligence as a positive and negative factor in global risk. In N. Bostrom, & M. M. Ćirković (Eds.), Global catastrophic risks. (Vol. 1, p. 184). New York: Oxford University Press. |
[103] | Złotowski, J., Yogeeswaran, K., & Bartneck, C. (2017). Can we control it? Autonomous robots threaten human identity, uniqueness, safety, and resources. International Journal of Human-Computer Studies, 100, 48-54. |
[25] | Fleming, D. A., Chong, A., & Bejarano, H. D. (2014). Trust and reciprocity in the aftermath of natural disasters. The Journal of Development Studies, 50(11), 1482-1493. |
[26] | Ford, M. R. (2009). The lights in the tunnel: Automation, accelerating technology and the economy of the future. Wayne, PA: Acculant Publishing. |
[27] |
Frankenberg, E., Nobles, J., & Sumantri, C. (2012). Community destruction and traumatic stress in post- tsunami Indonesia. Journal of Health and Social Behavior, 53(4), 498-514.
doi: 10.1177/0022146512456207 pmid: 22940603 |
[28] | Frey, C. B., Berger, T., & Chen, C. (2018). Political machinery: Did robots swing the 2016 US presidential election?. Oxford Review of Economic Policy, 34(3), 418-442. |
[29] | Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological Forecasting and Social Change, 114, 254-280. |
[30] |
Fuesting, M. A., Diekman, A. B., Boucher, K. L., Murphy, M. C., Manson, D. L., & Safer, B. L. (2019). Growing STEM: Perceived faculty mindset as an indicator of communal affordances in STEM. Journal of Personality and Social Psychology, 117(2), 260-281.
doi: 10.1037/pspa0000154 pmid: 30869983 |
[31] |
Fulford, D., Johnson, S. L., Llabre, M. M., & Carver, C. S. (2010). Pushing and coasting in dynamic goal pursuit: Coasting is attenuated in bipolar disorder. Psychological Science, 21(7), 1021-1027.
doi: 10.1177/0956797610373372 pmid: 20519486 |
[32] |
Gaesser, B., Shimura, Y., & Cikara, M. (2020). Episodic simulation reduces intergroup bias in prosocial intentions and behavior. Journal of Personality and Social Psychology, 118(4), 683-705.
doi: 10.1037/pspi0000194 pmid: 31157527 |
[33] |
Gamez-Djokic, M., & Waytz, A. (2020). Concerns about automation and negative sentiment toward immigration. Psychological Science, 31(8), 987-1000.
doi: 10.1177/0956797620929977 pmid: 32697627 |
[34] | Gordils, J., Elliot, A. J., Toprakkiran, S., & Jamieson, J. P. (2021). The effects of COVID-19 on perceived intergroup competition and negative intergroup outcomes. The Journal of Social Psychology, 161(4), 419-434. |
[35] | Goyal, A., & Aneja, R. (2020). Artificial intelligence and income inequality: Do technological changes and worker's position matter?. Journal of Public Affairs, 20(4), e2326. |
[36] | Gray, H. M., Gray, K., & Wegner, D. M. (2007). Dimensions of mind perception. Science, 315(5812), 619. |
[37] | Gray, K., Yam, K. C., Zhen’An, A. E., Wilbanks, D., & Waytz, A. (2023). The psychology of robots and artificial intelligence. In D. Gilbert et al (Eds.), Handbook of social psychology (pp. 1-83). Situational Press. |
[38] | Harari, Y. N. (2017). Reboot for the AI revolution. Nature, 550(7676), 324-327. |
[39] | Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press. |
[40] | Hirschberger, G., & Pyszczynski, T. (2011). Killing with a clean conscience:Existential angst and the paradox of morality. In M. Mikulincer & P. R. Shaver (Eds.), Social psychology of morality: Exploring the causes of good and evil (pp. 331-347). Washington, DC: American Psychological Association. |
[41] |
Howard, A., & Borenstein, J. (2018). The ugly truth about ourselves and our robot creations: The problem of bias and social inequity. Science and Engineering Ethics, 24(5), 1521-1536.
doi: 10.1007/s11948-017-9975-2 pmid: 28936795 |
[42] | Huang, H. L., Cheng, L. K., Sun, P. C., & Chou, S. J. (2021). The effects of perceived identity threat and realistic threat on the negative attitudes and usage intentions toward hotel service robots: The moderating effect of the robot’s anthropomorphism. International Journal of Social Robotics, 13, 1599-1611. |
[43] | Im, Z. J., Mayer, N., Palier, B., & Rovny, J. (2019). The “losers of automation”: A reservoir of votes for the radical right? Research & Politics, 6(1), 1-7. |
[44] | Jackson, J. C., Castelo, N., & Gray, K. (2020). Could a rising robot workforce make humans less prejudiced? American Psychologist, 75(7), 969-982. |
[45] | Jackson, J. W. (1993). Realistic group conflict theory: A review and evaluation of the theoretical and empirical literature. Psychological Record, 43(3), 395-413. |
[46] | Jetten, J., Mols, F., Healy, N., & Spears, R. (2017). “Fear of falling”: Economic instability enhances collective angst among societies’ wealthy class. Journal of Social Issues, 73(1), 61-79. |
[47] | Jetten, J., Mols, F., & Steffens, N. K. (2021). Prosperous but fearful of falling: The wealth paradox, collective angst, and opposition to immigration. Personality and Social Psychology Bulletin, 47(5), 766-780. |
[48] | Jetten, J., & Wohl, M. J. A. (2012). The past as a determinant of the present: Historical continuity, collective angst, and opposition to immigration. European Journal of Social Psychology, 42(4), 442-450. |
[49] | Kahn, B. (2023). Elon Musk and Apple cofounder Steve Wozniak among over 1, 100 who sign open letter calling for 6-month ban on creating powerful A.I. Retrieved August 17, 2024, from https://fortune.com/2023/03/29/elon-musk-apple-steve-wozniak-over-1100-sign-open-letter-6-month-ban-creating-powerful-ai/ |
[50] | Kahn, D. T., Björklund, F., & Hirschberger, G. (2022). The intent and extent of collective threats: A data-driven conceptualization of collective threats and their relation to political preferences. Journal of Experimental Psychology: General, 151(5), 1178-1198. |
[51] | Khasawneh, O. Y. (2018). Technophobia: Examining its hidden factors and defining it. Technology in Society, 54, 93-100. |
[52] | Kung, F. Y., Chao, M. M., Yao, D. J., Adair, W. L., Fu, J. H., & Tasa, K. (2018). Bridging racial divides: Social constructionist (vs. essentialist) beliefs facilitate trust in intergroup contexts. Journal of Experimental Social Psychology, 74, 121-134. |
[53] | Lalonde, R. N. (2002). Testing the social identity-intergroup differentiation hypothesis: We’re not American eh! British Journal of Social Psychology, 41(4), 611-630. |
[54] | Lasarov, W., & Hoffmann, S. (2020). Social moral licensing. Journal of Business Ethics, 165, 45-66. |
[55] | Leo, X., & Huh, Y. E. (2020). Who gets the blame for service failures? Attribution of responsibility toward robot versus human service providers and service firms. Computers in Human Behavior, 113, 106520. |
[56] | Li, J. J., Bonn, M. A., & Ye, B. H. (2019). Hotel employee's artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172-181. |
[57] | Li, J., & Huang, J. S. (2020). Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society, 63, 101410. |
[58] | Lin, J., Panganiban, A. R., Matthews, G., Gibbins, K., Ankeney, E., See, C.,... Long, M. (2022). Trust in the danger zone: Individual differences in confidence in robot threat assessments. Frontiers in Psychology, 13, 601523. |
[59] | Lucas, T., Rudolph, C., Zhdanova, L., Barkho, E., & Weidner, N. (2014). Distributive justice for others, collective angst, and support for exclusion of immigrants. Political Psychology, 35(6), 775-793. |
[60] | Mann, F. D., Krueger, R. F., & Vohs, K. D. (2020). Personal economic anxiety in response to COVID-19. Personality and Individual Differences, 167, 110233. |
[61] | Mathias, P. (2013). The first industrial nation: The economic history of Britain 1700-1914. London: Routledge. |
[62] | McClure, P. K. (2018). “You’re fired,” says the robot: The rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), 139-156. |
[63] |
McFarland, S., Webb, M., & Brown, D. (2012). All humanity is my ingroup: A measure and studies of identification with all humanity. Journal of Personality and Social Psychology, 103(5), 830-853.
doi: 10.1037/a0028724 pmid: 22708625 |
[64] | Merritt, A. C., Effron, D. A., & Monin, B. (2010). Moral self-licensing: When being good frees us to be bad. Social and Personality Psychology Compass, 4(5), 344-357. |
[65] | Miao, X., Liu, L., Dang, J., Wei, C., Huang, L., & Liu, Z. (2023). Unity or estrangement under crises? Perceived resource scarcity moderates the effect of a common threat on intergroup cooperation. Social Psychological and Personality Science, 15(5), 659-669. |
[66] |
Miloyan, B., Bienvenu, O. J., Brilot, B., & Eaton, W. W. (2018). Adverse life events and the onset of anxiety disorders. Psychiatry Research, 259, 488-492.
doi: S0165-1781(17)30520-6 pmid: 29154170 |
[67] | Neufeind, M., O’Reilly, J., & Ranft, F. (2018). Work in the digital age: Challenges of the fourth industrial revolution. London: Rowman and Littlefield. |
[68] | Osgood, J. M., & Muraven, M. (2015). Self-control depletion does not diminish attitudes about being prosocial but does diminish prosocial behaviors. Basic and Applied Social Psychology, 37(1), 68-80. |
[69] | Peng, K., Nisbett, R. E., & Wong, N. Y. C. (1997). Validity problems comparing values across cultures and possible solutions. Psychological Methods, 2(4), 329-344. |
[70] |
Penner, L. A., Dovidio, J. F., Piliavin, J. A., & Schroeder, D. A. (2005). Prosocial behavior: Multilevel perspectives. Annual Review of Psychology, 56, 365-392.
pmid: 15709940 |
[71] |
Riek, B. M., Mania, E. W., & Gaertner, S. L. (2006). Intergroup threat and outgroup attitudes: A meta-analytic review. Personality and Social Psychology Review, 10(4), 336-353.
pmid: 17201592 |
[72] | Roccas, S., & Amit, A. (2011). Group heterogeneity and tolerance: The moderating role of conservation values. Journal of Experimental Social Psychology, 47(5), 898-907. |
[73] | Römpke, A. K., Fritsche, I., & Reese, G. (2019). Get together, feel together, act together: International personal contact increases identification with humanity and global collective action. Journal of Theoretical Social Psychology, 3(1), 35-48. |
[74] | Rughiniş, C., Zamfirescu, R., Neagoe, A., & Rughiniş, R. (2018, April). Visions of robots, networks and artificial intelligence: Europeans’ attitudes towards digitisation and automation in daily life. In The international scientific conference eLearning and software for education (Vol. 2, pp. 114-119), Bucharest, Romania. |
[75] | Sherif, M. (1966). In common predicament: Social psychology of intergroup conflict and cooperation. New York: Houghton Mifflin. |
[76] | Shoss, M. K., & Ciarlante, K. (2022). Are robots/AI viewed as more of a workforce threat in unequal societies? Evidence from the eurobarometer survey. Technology, Mind, and Behavior, 3(2), 1-13. |
[77] | Sidanius, J. (1993). The psychology of group conflict and the dynamics of oppression:A social dominance perspective. In S. Iyengar & W. McGuire (Eds.), Explorations in political psychology (pp. 183-219). Durham, NC: Duke University Press. |
[78] | Simpson, B., & Willer, R. (2015). Beyond altruism: Sociological foundations of cooperation and prosocial behavior. Annual Review of Sociology, 41(1), 43-63. |
[79] |
Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: Why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89(6), 845-851.
pmid: 16393019 |
[80] | Stephan, W. G., Ybarra, O., & Morrison, K. R. (2009). Intergroup threat theory. In T. D. Nelson (Ed.), Handbook of prejudice (pp. 43-59). Mahwah, NJ: Lawrence Erlbaum. |
[81] | Sumner, W. G. (1906). Folkways: A study of mores, manners, customs and morals. Mineola, NY: Dover Publications. |
[82] | Susskind, R. E., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. New York: Oxford University Press. |
[83] | Tabri, N., Wohl, M. J. A., & Caouette, J. (2018). Will we be harmed, will it be severe, can we protect ourselves? Threat appraisals predict collective angst (and its consequences). European Journal of Social Psychology, 48(1), 72-85. |
[84] | Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel & W. G. Austin (Eds.), Psychology of Intergroup Relations (pp. 7-24). Chicago, IL: Nelson-Hall. |
[85] | Touré-Tillery, M., & Light, A. E. (2018). No self to spare: How the cognitive structure of the self influences moral behavior. Organizational Behavior and Human Decision Processes, 147, 48-64. |
[86] | Uenal, F., Sidanius, J., Roozenbeek, J., & Linden, S. (2021). Climate change threats increase modern racism as a function of social dominance orientation and ingroup identification. Journal of Experimental Social Psychology, 97, 104228. |
[87] | Vezzali, L., Andrighetto, L., Drury, J., Di Bernardo, G. A., & Cadamuro, A. (2017). In the aftermath of natural disasters:Fostering helping towards outgroup victims. In the aftermath of natural disasters: Fostering helping towards outgroup victims. In H. Zagefka & E. Van Leeuwen (Eds.), Intergroup helping: The positive side of intergroup behaviour (pp. 305-330). New York, NY: Springer. |
[88] | Vu, H. T., & Lim, J. (2021). Effects of country and individual factors on public acceptance of artificial intelligence and robotics technologies: A multilevel SEM analysis of 28-country survey data. Behaviour and Information Technology, 41(7), 1515-1528. |
[89] | Wohl, M. J. A., & Branscombe, N. R. (2008). Collective angst:How threats to the future vitality of the ingroup shape intergroup emotion. In H. A. Wayment & J. J. Bauer (Eds.), Transcending self-interest: psychological explorations of the quiet ego (pp. 171-181). Washington, DC: American Psychological Association |
[90] | Wohl, M. J. A., Branscombe, N. R., & Reysen, S. (2010). Perceiving your group’s future to be in jeopardy: Extinction threat induces collective angst and the desire to strengthen the ingroup. Personality and Social Psychology Bulletin, 36(7), 898-910. |
[91] | Wohl, M. J. A., Giguère, B., Branscombe, N. R., & McVicar, D. N. (2011). One day we might be no more: Collective angst and protective action from potential distinctiveness loss. European Journal of Social Psychology, 41(3), 289-300. |
[92] | Wohl, M. J. A., Squires, E. C., & Caouette, J. (2012). We were, we are, will we be? The social psychology of collective angst. Social and Personality Psychology Compass, 6(5), 379-391. |
[93] | World, Bank. (2011). World Bank national accounts data, and OECD National Accounts data files. Retrieved August 27, 2024, from https://data.worldbank.org/indicator/NY.GDP. MKTP.CD?end=2011&start=2011 |
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