Bibliographic Information
- Other Title
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- タゲンテキナ ショクギョウ トクセイ ニンチ ト シコウセイ ノ ソクテイ ショクギョウカン ルイジド データ ト MDS ニ ヨル ジゲン チュウシュツ ニ モトズイテ
- Measurement of Multi-Dimensional Cognitive Features of Occupation and Orientation : Similarity Data and Dimensions Extracted Using MDS
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Abstract
type:Thesis
This paper investigates the method to measure a multi-dimensional occupational orientation, based on the assumption that one's occupational orientation may be ascertained by the association between occupational features and one's preference for occupations. Prior researches relied on surveys with questions focusing on several specific occupational features that were thought to be important. However, such method world only allow the measurement of occupational orientation based on the pre-specified occupational features, and it excludes any other features that might also be relevant. The present study, therefore, first attempts to elicit latent dimensions of occupational features using a Multi-dimensional Scaling (MDS) technique. A survey of a small number of female college students was conducted. in which the respondents sorted various occupations into groups according to similarity (so-called a "pile-sort" method). The Multi-dimensional Scaling of judged similarities between all pairs of occupations extracted three latent cognitive dimensions of occupational features: "public interest," "skill," and "discretion." Next, the effects of these three dimensions on occupational preference were examined and they were found to be equally significant, verifying the existence of all three dimensions in the respondents' occupational orientations. Finally, these three dimensions were assessed in relation to the "status orientation" that has been considered important in previous studies.
Journal
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- 奈良女子大学社会学論集
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奈良女子大学社会学論集 12 1-16, 2007-03-01
奈良女子大学社会学研究会
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Details 詳細情報について
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- CRID
- 1050282813367646464
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- NII Article ID
- 110008581490
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- NII Book ID
- AN10436699
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- ISSN
- 13404032
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- NDL BIB ID
- 8770772
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- Text Lang
- ja
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- Article Type
- departmental bulletin paper
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- Data Source
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- IRDB
- NDL
- CiNii Articles