为探索残障人士在旅游景区就业的可能性,应用刻板印象研究中的BIAS Map(Behaviors from Intergroup Affect and Stereotypes Map)模型,基于对多个景区游客的问卷调查,运用方差分析和线性回归,剖析游客对旅游景区残障员工的态度及群际接...为探索残障人士在旅游景区就业的可能性,应用刻板印象研究中的BIAS Map(Behaviors from Intergroup Affect and Stereotypes Map)模型,基于对多个景区游客的问卷调查,运用方差分析和线性回归,剖析游客对旅游景区残障员工的态度及群际接触因素对游客态度的影响。研究表明,从游客态度角度看,残障人士在旅游景区工作有其可能性。其原因是:游客对旅游景区雇佣的残障员工总体上持高热情、低能力的刻板印象,会唤醒游客对残障员工的钦佩情绪及采取被动助长残障员工的行为;在排除人口统计特征的影响下,接受过残障人士的服务、与残障人士高频率接触会显著唤醒游客对残障员工的积极情绪。建议强化地方政府在促进残障人士就业过程中的主导作用,倡导景区雇佣残障人士,重视“全国助残日”等节日契机,促进公众与残障群体多方式、高频率的接触,从而减少社会偏见,构建和谐社会。展开更多
This study evaluates the performance of 15 Coupled Model Intercomparison Project Phase 6(CMIP6)models(before and after downscaling)in simulating autumn precipitation extremes in Southwest China based on a high-resolut...This study evaluates the performance of 15 Coupled Model Intercomparison Project Phase 6(CMIP6)models(before and after downscaling)in simulating autumn precipitation extremes in Southwest China based on a high-resolution,statistically downscaled CMIP6 dataset,using the CN05.1 dataset as a reference.The Bias Correction Constructed Analogues with Quantile mapping reordering(BCCAQ)method used in deriving the downscaled CMIP6 dataset significantly enhances the models'abilities to reproduce the spatial patterns of the extreme precipitation indices,particularly for total precipitation,number of moderate rain days(R10),and number of heavy rain days(R20).Notable improvements are also observed for maximum 1-day precipitation(RX1),maximum 5-day precipitation(RX5),and simple daily intensity index(SDII),alongside reduced inter-model spread and systematic biases.Bias correction also improves the simulation of interannual variability,substantially reducing the root mean square error(RMSE)for total precipitation,R10,and R20.Increased interannual variability in the future is expected for certain indices,spatially concentrated for RX1 and RX5 in the south and R20 in the east.Projections using the bias-corrected multi-model ensemble under the SSP2-4.5 and SSP5-8.5 scenarios indicate a significant intensification of autumn extreme precipitation in both intensity-and frequency-related indices by the 2080s,especially in southern Southwest China,with precipitation becoming more concentrated in heavier events.Consecutive dry days(CDDs)exhibit spatial variability with an observed increase in the southeast,while consecutive wet days(CWDs)shows no significant change.These findings highlight an increased risk of intensified autumn rainfall and altered precipitation patterns in the region under future climate change.展开更多
文摘为探索残障人士在旅游景区就业的可能性,应用刻板印象研究中的BIAS Map(Behaviors from Intergroup Affect and Stereotypes Map)模型,基于对多个景区游客的问卷调查,运用方差分析和线性回归,剖析游客对旅游景区残障员工的态度及群际接触因素对游客态度的影响。研究表明,从游客态度角度看,残障人士在旅游景区工作有其可能性。其原因是:游客对旅游景区雇佣的残障员工总体上持高热情、低能力的刻板印象,会唤醒游客对残障员工的钦佩情绪及采取被动助长残障员工的行为;在排除人口统计特征的影响下,接受过残障人士的服务、与残障人士高频率接触会显著唤醒游客对残障员工的积极情绪。建议强化地方政府在促进残障人士就业过程中的主导作用,倡导景区雇佣残障人士,重视“全国助残日”等节日契机,促进公众与残障群体多方式、高频率的接触,从而减少社会偏见,构建和谐社会。
基金Supported by the Chongqing Natural Science Foundation(CSTB2022NSCQ-MSX0558)Chongqing Meteorological Department Talent Support Project(RCZC-202303)。
文摘This study evaluates the performance of 15 Coupled Model Intercomparison Project Phase 6(CMIP6)models(before and after downscaling)in simulating autumn precipitation extremes in Southwest China based on a high-resolution,statistically downscaled CMIP6 dataset,using the CN05.1 dataset as a reference.The Bias Correction Constructed Analogues with Quantile mapping reordering(BCCAQ)method used in deriving the downscaled CMIP6 dataset significantly enhances the models'abilities to reproduce the spatial patterns of the extreme precipitation indices,particularly for total precipitation,number of moderate rain days(R10),and number of heavy rain days(R20).Notable improvements are also observed for maximum 1-day precipitation(RX1),maximum 5-day precipitation(RX5),and simple daily intensity index(SDII),alongside reduced inter-model spread and systematic biases.Bias correction also improves the simulation of interannual variability,substantially reducing the root mean square error(RMSE)for total precipitation,R10,and R20.Increased interannual variability in the future is expected for certain indices,spatially concentrated for RX1 and RX5 in the south and R20 in the east.Projections using the bias-corrected multi-model ensemble under the SSP2-4.5 and SSP5-8.5 scenarios indicate a significant intensification of autumn extreme precipitation in both intensity-and frequency-related indices by the 2080s,especially in southern Southwest China,with precipitation becoming more concentrated in heavier events.Consecutive dry days(CDDs)exhibit spatial variability with an observed increase in the southeast,while consecutive wet days(CWDs)shows no significant change.These findings highlight an increased risk of intensified autumn rainfall and altered precipitation patterns in the region under future climate change.
