Patent Publication Number: US-11657357-B2

Title: Computer implemented method for personal attribute valuation and matching with occupations and organizations

Description:
This United States Non-Provisional patent application claims the benefit of U.S. Provisional Patent Application No. 61/947,301, filed Mar. 3, 2014, hereby incorporated by reference herein. 
    
    
     I. BACKGROUND 
     Conventional methodologies of assessing person to occupation fit may rely on correlations which lack a meaningful measure to quantify the relationship between the person and the occupation in a manner unaffected by the form of the relationship linear or non-linear, as well as other confounding factors which affect the correlation value as described by Goodwin, L. D., &amp; Leech, N. L. in: Understanding correlation: Factors that affect the size of r.  Journal of Experimental Education,  2006, 74, 251-266, and many of the problems with simple correlations between profiles as discussed by Edwards, J. R. Person-job fit: A conceptual integration, literature review, and methodological critique. In C. L. Cooper &amp; I. T. Robertson (Eds.),  International review of industrial and organizational psychology,  1991, vol. 6, pp. 283-357, New York: Wiley. 
     II. SUMMARY OF THE INVENTION 
     Accordingly, a broad object of embodiments of the invention can be to provide a computer implemented system and method for personal attribute valuation and fit of a user to one or more occupations. The system takes the form of computer elements and computer code which function to allow a user to assess user values and user interests relevant to an occupation and transforms the assessed user values and user interests to corresponding user values scores and user interest scores. The computer code further functions to compare the user values scores and user interests scores to standardized occupation values scores and occupation interests scores for a plurality of occupations retrievably stored in a server computer. The computer code includes a scoring algorithm which functions to calculate a user-occupation fit score (a congruence index) which provides an objective measure of user to occupation fit by comparing user values scores and user interests scores with derived standardized (ideal) occupation values scores and occupation interest scores for one or a plurality of occupations. The user-occupation fit score provides a meaningful fit measure which quantifies the suitability of a user in relation to a plurality of occupations. 
     Another broad object of embodiments of the invention can be to provide a computer implemented system and method for personal attribute valuation and fit of a user to one or more organizations. The system takes the form of computer elements and computer code which function to allow a user or an organization to assess user values, user interests, and user workplace preferences relevant to an occupation or an organization and transforms the assessed user values, user interests, and user workplace preferences to corresponding user values scores, user interest scores, and user workplace preferences scores. The computer code further functions to compare the user work values scores, user interests scores, and workplace preferences scores to organization values scores, organization interest scores, and organization workplace preferences scores retrievably stored in a server computer. The computer code includes a scoring algorithm which functions to calculate a user-organization fit score (a congruence index) which provides an objective measure of user to organization fit by comparing user values scores, user interests scores, and user workplace preferences scores with derived standardized (ideal) organization values scores, organization interest scores, and organization workplace preferences scores for one or a plurality of organizations. The user-organization fit score provides a meaningful fit measure which quantifies the suitability of a user in relation to one or more occupations. 
     Naturally, further objects of the invention are disclosed throughout other areas of the specification, drawings, photographs, and claims. 
    
    
     
       III. A BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a particular embodiment of an inventive computer implemented system for personal attribute valuation and fit with occupations and organizations. 
         FIG.  2    is a block diagram of an illustrative computer elements, network elements and computer-readable medium which provides computer-executable instructions to provide embodiments of the inventive computer implemented system for personal attribute valuation and fit with occupations and organizations. 
         FIG.  3    is an illustration of particular embodiment of an interactive graphic user interface including an interactive graphical user interface image which displays a plurality of user attribute category icons which by click event retrieve instructions and user attribute assessment instruments. 
         FIG.  4    is an illustration of a particular embodiment of an interactive graphical user interface image including a values assessment instruction which by click event allows execution of the program code to further display a values assessment instrument. 
         FIG.  5    is an illustration of a particular embodiment of an interactive graphical user interface image including a values assessment instrument. 
         FIG.  6    is an illustration of a particular embodiment of an interactive graphical user interface image including a user values scores graph which plots calculated user value scores for assessed user values. 
         FIG.  7    is an illustration of a particular embodiment of an interactive graphical user interface image including an interests assessment instruction which by click event allows execution of the program code to further display a interests assessment instrument. 
         FIG.  8    is an illustration of a particular embodiment of an interactive graphical user interface image including an interests assessment instrument. 
         FIG.  9    is an illustration of a particular embodiment of an interactive graphical user interface image including a user interest scores graph which plots calculated user interest scores for assessed user interests. 
         FIG.  10    is an illustration of a particular embodiment of an interactive graphical user interface image including a personality assessment instruction which by click event allows execution of the program code to further display a personality assessment instrument. 
         FIG.  11    is an illustration of a particular embodiment of an interactive graphical user interface image including a personality assessment instrument. 
         FIG.  12    is an illustration of a particular embodiment of an interactive graphical user interface image including a user personality scores graph which plots calculated user personality scores for assessed user personality characteristics. 
         FIG.  13    is an illustration of a particular embodiment of an interactive graphical user interface image including a workplace preferences assessment instruction which by click event allows execution of the program code to further display a workplace preferences assessment instrument. 
         FIG.  14    is an illustration of a particular embodiment of an interactive graphical user interface image including a workplace preferences assessment instrument. 
         FIG.  15    is an illustration of a particular embodiment of an interactive graphical user interface image including a user workplace preferences scores graph which plots calculated user workplace preference scores for assessed user workplace preferences. 
         FIG.  16    is an illustration of a particular embodiment of an interactive graphical user interface image including an occupation fit filter display area and an occupation fit display area which by click event activates occupation fit filters and initiates an occupation data retrieval request to retrieve one or more occupation identifiers based on user occupation fit scores. 
         FIG.  17 A  is an illustration of a particular embodiment of an interactive graphical user interface image which includes alternative occupation titles. 
         FIG.  17 B  is an illustration of a particular embodiment of an interactive graphical user interface image which includes a description of an occupation. 
         FIG.  18    is an illustration of a particular embodiment of an interactive graphical user interface image which by click event allows weighted use of both user-occupation fit and user-organization fit metrics in comparing a plurality of users against one or a plurality of occupations. 
         FIG.  19    is an illustration of a particular embodiment of an interactive graphical user interface image which by click event allows weighted use of both user-occupation fit and user-organization fit metrics in comparing a plurality of users against one or a plurality of occupations. 
         FIG.  20    is an illustration of a user fit profile retrieved by click event of user identifiers in the graphical user interface shown in  FIG.  19   . 
         FIG.  21    is an illustration of an interactive graphical user interface image which by click event displays a fit report based on user scores compared to the occupation scores or organization scores for a particular occupation. 
         FIG.  22    is an illustration of a graphical user interface image which by click event displays a detailed fit analysis comparing how occupation scores compare to user scores of the user chosen for an occupation. 
         FIG.  23    is an illustration of a graphical user interface image which by click event displays a interview questions based on the occupation and user scores. 
     
    
    
     IV. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Now referring to primarily to  FIGS.  1  and  2   , one or more client devices ( 1 ) can be configured to connect with one or more server computers ( 2 ) through a wide area network (“WAN”) ( 3 ), such as the Internet ( 4 ), or one or more local area networks ( 5 )(“LAN”) to transfer digital data ( 6 ). As to particular embodiments, the one or more client devices ( 1 ) can take the form of a limited-capability computer designed specifically for navigation on a WAN ( 3 ) such as the Internet ( 4 ). Alternatively, the one or more client devices ( 1 ) might be set-top boxes, intelligent televisions connected to receive digital data ( 6 ) through an entertainment medium such as a cable television network or a digital satellite broadcast, hand-held devices such as smart phones, slate or pad computers, personal digital assistants or camera/cell phone, or multiprocessor systems, microprocessor-based or programmable consumer electronics, network personal computers, minicomputers, mainframe computers, or the like, or a combination thereof. 
     Again referring primarily to  FIGS.  1  and  2   , in general, each of the one or more client devices ( 1 ) can include a browser ( 7 ) such as Microsoft&#39;s INTERNET EXPLORER®, GOOGLE CHROME®, MOZILLA FIREFOX®, or the like, which functions to download and render multimedia content that is formatted in “hypertext markup language” (HTML). In this environment, a first server computer ( 8 ) can include an computer code ( 9 ) which in part includes a “personal attribute valuation and matching program” containing a graphical user interface module ( 10 ) executable to implement the most significant portions of a graphical user interface ( 11 ). As to these embodiments, the graphical user interface module ( 10 ) which implements the graphical user interface ( 11 ) can be resident in the first server computer ( 8 )(as shown in the examples of  FIGS.  1  and  2   ) and the one or more client devices ( 1 ) can use the browser ( 7 ) to simply display downloaded content and to relay user inputs ( 12 ) back to the first server computer ( 8 ). The first server computer ( 8 ) would respond by formatting new graphical user interface images ( 13 ) (as shown in the illustrative examples of  FIGS.  3  through  21   ) and downloading graphical user interface images ( 13 ) for display on the display surface ( 14 ) associated with the one or more of the client devices ( 1 ). 
     In other embodiments, the one or more server computers ( 1 ) can be used primarily as sources of digital data ( 6 ), with primary responsibility for implementing the graphical user interface ( 11 ) placed upon each of the client devices ( 1 ). As to these embodiments, each of the one or more client devices ( 1 ) can store or run the computer code ( 9 ) implementing the graphical user interface ( 11 ) and retrieve digital data ( 6 ) from the one more server computers ( 2 ). While illustrative examples in this description may attribute a certain type of digital data ( 6 ) to a certain server computer ( 2 ) for clarity, it is to be understood that various types of digital data ( 6 ) may reside in one server computer ( 2 ) or one type of digital data ( 6 ) can be distributed among a plurality of server computers ( 2 ) and embodiments of the invention can utilize a lesser or greater number of server computers ( 2 ) to a lesser or greater extent depending upon the application. The computer code ( 9 ) further operates to provide digital data ( 6 ) obtained from one or more server computers ( 2 ) in a common format, as further described below. 
     A user ( 16 ) can enter commands and information into one or more client devices ( 1 ) through input devices ( 17 ) such as a keyboard ( 18 ) or a pointing device ( 19 ) such as a mouse ( 20 ); however, any method or device that converts user ( 16 ) action into commands and information can be utilized including, but not limited to: a microphone, joystick, game pad, touch screen, or the like. The display surface ( 14 ) such as a monitor screen or other type of display device can also be connected to a bus ( 21 ) via a video display interface ( 22 ), such as a video adapter, or the like. The graphical user interface ( 11 ) can in part be presented as one or more interactive graphical user interface images ( 13 ) on the display surface ( 14 ). In addition to the display surface ( 14 ), each of the one or more client devices ( 1 ) can further include other peripheral output devices ( 23 ) such as speakers ( 24 ) and printers ( 25 ), or the like, or combinations thereof. 
     Now referring primarily to  FIG.  2   , an illustrative example of a client device ( 1 ) includes a processing unit ( 26 ), a memory element ( 27 ), and a bus ( 21 ) which operably couples components of the client device ( 1 ), including without limitation the memory element ( 27 ) to the processing unit ( 26 ). The processing unit ( 26 ) can comprise one central-processing unit (CPU), or a plurality of processing units which operate in parallel to process digital information. The bus ( 21 ) may be any of several types of bus configurations including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The memory element ( 27 ) can without limitation be one or more of a read only memory (ROM) ( 28 ) or a random access memory (RAM) ( 29 ), or a combination thereof. A basic input/output system (BIOS) ( 30 ), containing routines that assist transfer of data between the components of the client device ( 1 ), such as during start-up, can be stored in ROM ( 28 ). The client computer ( 1 ) can further include a hard disk drive ( 31 ) for reading from and writing to a hard disk ( 32 ), a magnetic disk drive ( 33 ) for reading from or writing to a removable magnetic disk ( 34 ), and an optical disk drive ( 35 ) for reading from or writing to a removable optical disk ( 36 ) such as a CD ROM or other optical media. The hard disk drive ( 31 ), magnetic disk drive ( 33 ), and optical disk drive ( 35 ) can be connected to the bus ( 21 ) by a hard disk drive interface ( 37 ), a magnetic disk drive interface ( 38 ), and an optical disk drive interface ( 39 ), respectively. The memory element ( 27 ) or the drives ( 37 )( 38 )( 39 ) and their associated computer-readable media ( 32 )( 34 )( 36 ) provide nonvolatile storage of computer-readable instructions, data structures, program modules and other digital data ( 15 ) for the client device ( 1 ). It can be appreciated by those skilled in the art that any type of computer-readable media that can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, random access memories (RAMs), read only memories (ROMs), and the like, may be used in a variety of operating environments. The computer code ( 9 ) whether in part, as to particular computer program modules, or in whole may be stored on or included in the hard disk drive ( 33 ), magnetic disk ( 34 ), optical disk ( 36 ), ROM ( 28 ), or RAM ( 29 ), including an operating system ( 40 ), one or a plurality of application programs ( 41 ) including the inventive personal attribute valuation and matching program ( 42 ) which implements the graphical user interface ( 11 ) or other program interfaces. 
     A “click event” occurs when the user ( 16 ) operates a function of the computer code ( 9 ) through the use of a command which for example can include pressing or releasing a left mouse button ( 43 ) while a pointer ( 44 ) is located over a control icon ( 45 )(or other interactive field which activates a function of the computer code ( 9 )) displayed in a graphical user interface image ( 13 ) of the graphical user interface ( 11 ). However, it is not intended that a “click event” be limited to the press and release of the left button ( 43 ) on a mouse ( 20 ) while a pointer ( 44 ) is located over a control icon ( 45 )(or field), rather, a “click event” is intend to broadly encompass a command by the user ( 16 ) through which a function of computer code ( 9 )(whether one or more of a program, an application, a module, or the like) including that portion of the computer code ( 9 ) which implements the graphical user interface ( 11 ) can be activated or performed whether through selection of one of a plurality of control icon(s) ( 45 ) or fields, or by user voice command, keyboard stroke, mouse button, touch on a touch screen, or otherwise. It is further intended that control icons ( 45 ) can be configured or displayed in any configuration such as a bullet, a point, a circle, a triangle, a square, a polygon (or other geometric configurations or combinations thereof), or as fields or boundary elements created in graphical user interface images ( 13 ), or as fields in which locations, addresses, or other terms can be entered manually or by operation of the computer code ( 9 ), or a portion or element thereof, such as: a street address, a zip code, a county code, a natural area code, a latitude/longitude, projected coordinate X and Y, or other notation, script, character, or the like. 
     The client computer ( 1 ) may operate in a networked environment using one or more logical connections ( 46 ) to connect to one or more of server computers ( 2 ). These logical connections ( 46 ) can be achieved by one or more communication devices ( 47 ) coupled to or a part of the client device ( 1 ); the invention is not limited to a particular type of communications device ( 47 ). The one or more server computers ( 2 ) can be another computer, a server, a router, a network PC, a client, a peer device or other common network node, and can include a part or all of the elements above-described relative to the client device ( 1 ). The logical connections ( 46 ) depicted in  FIG.  2    can include a LAN ( 5 ) or a WAN ( 4 ). Such networking environments are commonplace and include for example: enterprise-wide computer networks, intranets, wireless networks, global satellite networks, cellular phone networks and the Internet ( 4 ), or the like. 
     When used in a LAN-networking environment, the client device ( 31 ) can be connected to the LAN ( 5 ) through a network interface ( 48 ) or adapter, which is one type of communications device ( 47 ). When used in a WAN-networking environment, the client device ( 1 ) typically includes a modem ( 49 ), a type of communications device ( 47 ), or other type of communications device for establishing communications over the WAN ( 3 ), such as the Internet ( 4 )(as shown in the example of  FIGS.  1  and  2   ). The modem ( 49 ), which may be internal or external, is connected to the bus ( 21 ) via a serial port interface ( 50 ). In a networked environment, program modules depicted relative to the client device ( 1 ), or portions thereof, may be as to certain embodiments of the invention be stored in the one or more server computers ( 2 ) (as shown in the examples of  FIGS.  1  and  2   ). It is appreciated that the network connections shown are exemplary and other elements of and communications devices for establishing a communications link between the client devices ( 1 ) and the server computers ( 2 ) can be used. 
     Again referring primarily to  FIGS.  1  and  2   , the client device ( 1 ) can encompass a single client computer or can encompass a plurality of client devices each of which can be operated by a user ( 16 ). The user ( 16 ) can access the computer code ( 9 ) including the personal attribute valuation and matching program ( 42 ) containing the graphical user interface module ( 10 ) that implements the graphical user interface ( 11 ) allowing retrieval of digital data ( 6 ) from one or more server computers ( 2 ) in a common format for display in or as a part of the graphical user interface ( 11 ) on the display surface ( 14 ) of the client device ( 1 ). 
     Now referring to  FIGS.  3  through  21   , which provide illustrative exemplary embodiments of the apparatus and method inventive graphical user interface ( 11 ) including one or more graphical user interface images ( 13 ) generated by the graphical user interface module ( 10 ). The graphical user interface ( 11 ) can be implemented using various technologies and different devices, depending on the preferences of the designer and the particular efficiencies desired for a given circumstance. 
     Now referring primarily to  FIGS.  1  through  15   , a user ( 16 ) can use the browser ( 7 ) of a client device ( 1 ) to download the computer code ( 9 ) in whole or in part including the inventive personal attribute valuation and matching program ( 42 ) from a server computer ( 2 ) to the memory element ( 27 ) of the client device ( 1 ). A processor ( 26 ) in communication with the memory element ( 27 ) of the client device ( 1 ) can execute the relevant portions of the computer code ( 9 ) to display an interactive graphical user interface ( 11 ) including one or more interactive graphical user interface images ( 13 ) which can be serially presented on the display surface ( 14 ) associated with the client device ( 1 ). The user ( 16 ) by click event in the one or more interactive graphical user interface images ( 13 ) can relay user inputs ( 12 ) back to the server computer ( 2 ) or client device ( 1 ). The client device ( 1 ) or server computer ( 2 ) can respond by formatting additional interactive graphical user interface images ( 13 ) for display on the display surface ( 14 ) of the client device ( 1 ). 
     Embodiments of the interactive graphical user interface images ( 13 ) can by click event be used to execute the inventive personal attribute valuation and matching program ( 42 ) of the program code ( 9 ) to assess one or more user attributes ( 51 ) of the user ( 16 ) which by further execution of the computer code ( 9 ) can be transformed into user attribute scores ( 52 ) which by comparison to occupation attribute scores ( 53 ) allows calculation of corresponding occupation-user fit scores ( 54 ) for the assessed one or more user attributes ( 51 ) of the user ( 16 ). 
     Now referring primarily to  FIG.  3   , an illustrative example of the interactive graphical user interface ( 11 ) is shown which includes one or more user attribute category icons ( 55 ) corresponding to one more user attribute categories ( 56 ) (as shown in the example of  FIG.  3    “Values”, “Interests”, “Personality” and “Workplace Preferences”). A user attribute category icon ( 55 ) can by click event execute the program code ( 9 ) to retrieve one or more user attribute assessment instruments ( 57 ) stored in a server computer ( 2 ). The user attribute assessment instruments ( 57 ) can be used to measure the corresponding user attribute ( 51 ) of the selected user attribute category ( 56 ). 
     For example, by click event of a values category icon ( 58 ) (one of the user attribute category icons ( 55 )), the program code ( 9 ) can be executed to display a values assessment instruction ( 59 ) (as shown in the example of  FIG.  4   ) which allows execution of the program code ( 9 ) by click event to retrieve and display a values assessment instrument ( 60 ). The values assessment instrument ( 60 ) accessible by the user ( 16 ) as one or more interactive graphical user interface images ( 13 ) allows assessment of user values ( 61 ) relevant to an occupation ( 138 ) (as shown in the example of  FIG.  5   ). A values assessment instrument ( 60 ) suitable for use with embodiments of the invention can be an O*NET Work Importance Locator published by the United States Department of Labor Employment and Training Administration, hereby incorporated by reference, which measures six user values ( 61 ) drawn from “The Theory of Work Adjustment,” Dawis and Lofquist in:  A psychological theory of work adjustment . Minneapolis: University of Minnesota Press, 1984, hereby incorporated by reference (“Achievement” ( 62 ), “Independence” ( 63 ), “Recognition” ( 64 ), “Relationships” ( 65 ), “Support” ( 66 ), and “Working Conditions” ( 67 ), as shown in the example of  FIG.  6   ). The values assessment instrument ( 60 ) can be configured to operate by click event to allow the user ( 16 ) to place in priority order one or more value statements ( 68 ). The embodiment of the graphical user interface ( 11 ) shown in the example of  FIG.  5    allows use of a pointer ( 44 ) to drag and drop the value statements ( 68 ) into priority order from top to bottom in a list of value statements ( 69 ). 
     The user ( 16 ) by click event of a values submission icon ( 70 ) can submit the completed values assessment instrument ( 60 ) to activate a values score value calculator ( 71 ) which functions to transform the user values ( 61 ) assessed by use of the values assessment instrument ( 60 ) into user values scores ( 72 ) for each of the six user values ( 61 ). The computer code ( 9 ) can further function to generate a user values scores graph ( 73 ) which allows ready comparison of each of the calculated user value scores ( 72 ) for the six user values ( 61 )(as shown in the example of  FIG.  6    as a bar graph which plots each of the user values scores ( 72 ) for “Achievement” ( 62 ), “Independence” ( 63 ), “Recognition” ( 64 ), “Relationships” ( 65 ), “Support” ( 66 ), and “Working Conditions” ( 67 ). 
     Again referring primarily to  FIG.  3   , the user ( 16 ) by click event of an interests category icon ( 74 ) can execute the program code ( 9 ) to display an interest assessment instruction ( 75 ) (as shown in the example of  FIG.  7   ). The user by click event can execute the program code ( 9 ) to further retrieve and display an interests assessment instrument ( 76 ) from a memory element ( 27 ) as one or more interactive graphical user interface images ( 13 ) (as shown in the example of  FIG.  8   ). The interests assessment instrument ( 76 ) accessible by the user ( 16 ) as one or more interactive graphical user interface images ( 13 ) allows the assessment of user interests ( 77 ) relevant to an occupation ( 138 ) (as shown in the example of  FIG.  7   ). An interest assessment instrument ( 76 ) suitable for use with embodiments of the invention can be the O*NET Interest Profiler published by the United States Department of Labor Employment and Training Administration, hereby incorporated by reference herein, which measures six user interests ( 72 ) drawn from “RIASEC Theory Of Vocational Types,” Holland,  Making vocational choices: A theory of vocational personalities and work environments  (3rd ed.). Odessa, FL: Psychological Assessment Resources, 1997, hereby incorporated by reference herein (“Realistic” ( 78 ), “Investigative” ( 79 ), “Artistic” ( 80 ), “Social” ( 81 ), “Enterprising” ( 82 ), and “Conventional” ( 83 )). The interests assessment instrument ( 76 ) can be configured to operate by click event to associate each of a plurality of interest statements ( 84 ) with one of a plurality interest valuation statements ( 85 )(shown in the example of  FIG.  8    as “Strongly Dislike” ( 86 ), “Dislike” ( 87 ), “Unsure” ( 88 ), “Like” ( 89 ), or “Strongly Like” ( 90 )). The embodiment of the graphical user interface ( 11 ) shown in the example of  FIG.  8    allows use of a pointer ( 44 ) to selectably darken a bullet ( 91 ) associated with one of the listed interest valuation statements ( 80 ). 
     The user ( 16 ) by click event of an interest submission icon ( 92 ) can submit the completed interests assessment instrument ( 76 ) to activate an interest score calculator ( 93 ) which functions to transform the user interests ( 77 ) assessed by use of the interests assessment instrument ( 76 ) into each of the user interest scores ( 94 ) for each of the user interests ( 72 ). As to particular embodiments, the interest score calculator ( 93 ) operates to generate user interest scores ( 94 ) for each of the six user interests ( 77 ) (“Realistic” ( 78 ), “Investigative” ( 79 ), “Artistic” ( 80 ), “Social” ( 81 ), “Enterprising” ( 82 ), and “Conventional” ( 83 )). The computer code ( 9 ) can further function to generate a user interests scores graph ( 95 ) which allows ready comparison of user interests scores ( 94 ) for each of the calculated user interests ( 77 )(as shown in the example of  FIG.  9    as a bar graph which plots each of the user assessment interests scores ( 89 ) for “Realistic” ( 78 ), “Investigative” ( 79 ), “Artistic” ( 80 ), “Social” ( 81 ), “Enterprising” ( 82 ), and “Conventional” ( 83 )). 
     Again referring primarily to  FIG.  3   , by click event of a personality category icon ( 96 ), the program code ( 9 ) can be executed to display a personality assessment instruction ( 92 ) (as shown in the example of  FIG.  10   ) which allows execution of the program code ( 9 ) by click event to retrieve and display a personality assessment instrument ( 98 ) as an interactive graphical user interface images ( 13 ) (as shown in the example of  FIG.  11   ). The personality assessment instrument ( 98 ) accessible by the user ( 16 ) as one or more interactive graphical user interface images ( 13 ) allows the assessment of user personality characteristics ( 99 ) relevant to an occupation ( 138 ) (as shown in the example of  FIG.  11   ). A personality assessment instrument ( 98 ) suitable for use with embodiments of the invention can be the “Questionnaire Format for Administering the 50-Item Set of IPIP Big-Five Factor Markers” published by Goldberg, 1992, hereby incorporated by reference, which measures five user personality characteristics ( 99 ) (shown in the example of  FIG.  12    as “Openness to Experience” ( 100 ), “Conscientiousness” ( 101 ), “Extraversion” ( 102 ), “Agreeableness” ( 103 ) and “Negative Emotionality” ( 104 )). The personality assessment instrument ( 98 ) can be configured to operate by click event to associate each of a list of personality statements ( 105 ) with one of a list of personality valuation statements ( 106 ) (as shown in the example of  FIG.  11    as “Very Inaccurate” ( 107 ), “Moderately Accurate” ( 108 ), “Neither Accurate nor Inaccurate” ( 109 ), “Moderately Accurate” ( 110 ), or “Very Accurate” ( 111 )). The embodiment of the graphical user interface ( 11 ) shown in the example of  FIG.  11    allows use of a pointer ( 44 ) to selectably darken a bullet ( 91 ) associated with one of the listed personality valuation statements ( 106 ). 
     The user ( 16 ) by click event of a personality assessment submission icon ( 112 ) can submit the completed personality assessment instrument ( 98 ) to activate a personality score calculator ( 113 ) which functions to transform the user personality characteristics ( 99 ) assessed by use of the personality assessment instrument ( 98 ) in to user personality scores ( 114 ) for each of the user personality characteristics ( 94 ). As to particular embodiments, the personality score calculator ( 113 ) operates to generate user personality scores ( 114 ) for each of the five user personality characteristics ( 99 )(“Openness to Experience” ( 100 ), “Conscientiousness” ( 101 ), “Extraversion” ( 102 ), “Agreeableness” ( 103 ) and “Negative Emotionality” ( 104 )). The computer code ( 9 ) can further function to generate a user personality characteristics scores graph ( 115 ) which allows ready comparison of each of the calculated user personality characteristics ( 99 )(as shown in the example of  FIG.  12    as a bar graph which plots each of the user personality scores ( 114 ) for “Openness to Experience” ( 100 ), “Conscientiousness” ( 101 ), “Extraversion” ( 102 ), “Agreeableness” ( 103 ) and “Negative Emotionality” ( 104 )). 
     Again referring primarily to  FIG.  3   , by click event of a workplace preferences category icon ( 116 ), the program code ( 9 ) can be executed to display a workplace preferences assessment instruction ( 117 ) (as shown in the example of  FIG.  13   ) which allows execution of the program code ( 9 ) by click event to retrieve and display a workplace preferences assessment instrument ( 118 ) as one or more interactive graphical user interface images ( 13 ) (as shown in the example of  FIG.  14   ). The workplace preferences assessment instrument ( 118 ) accessible by the user ( 16 ) as one or more interactive graphical user interface images ( 13 ) allows the assessment of user workplace preferences ( 119 ) relevant to an occupation ( 138 ) or an organization ( 173 )(as shown in the example of  FIG.  14   ). A workplace preferences assessment instrument ( 118 ) suitable for use with embodiments of the invention can be the Organizational Culture Profile-Revised published by Sarros, Gray, Densten, and Cooper in: The Organizational Culture Profile Revisited and Revised: An Australian Perspective.  Australian Journal of Management,  2005, 30, 159, hereby incorporated by reference herein, which measures six user workplace preferences ( 119 )(shown in the example of  FIG.  15    as “Competiveness” ( 119 ), “Social Responsibility” ( 120 ), “Supportiveness” ( 121 ), “Innovation” ( 122 ), Emphasis on Rewards” ( 123 ), “Performance Orientation” ( 124 ), and “Stability” ( 125 )). The workplace assessment instrument ( 119 ) can be configured to operate by click event to associate each of a plurality of work place preference statements ( 127 ) with one of a list of work place preference valuation statements ( 128 ) (shown in the example of  FIG.  14    as “Not At All” ( 129 ), “Minimally” ( 130 ), “Moderately” ( 131 ), “Considerably” ( 132 ), or “Very Much” ( 133 )). The embodiment of the graphical user interface ( 11 ) shown in the example of  FIG.  14    allows use of a pointer ( 44 ) to selectably darken a bullet ( 91 ) associated with one of the listed workplace preference valuation statements ( 127 ). 
     The user ( 16 ) by click event of a workplace preferences assessment submission icon ( 134 ) can submit the completed workplace preferences assessment instrument ( 118 ) to activate a workplace preferences score calculator ( 135 ) which functions to transform the user workplace preferences ( 119 ) assessed by use of the workplace preferences assessment instrument ( 118 ) into user workplace preferences scores ( 136 ) for each of the six user workplace preferences ( 119 ). As to particular embodiments, the workplace preferences score calculator ( 135 ) operates to generate user workplace preferences scores ( 136 ) for each of the six workplace preferences ( 119 ) “Competiveness” ( 120 ), “Social Responsibility” ( 121 ), “Supportiveness” ( 122 ), “Innovation” ( 123 ), Emphasis on Rewards” ( 124 ), “Performance Orientation” ( 125 ), and “Stability” ( 126 ). The computer code ( 9 ) can further function to generate a user workplace preferences scores graph ( 137 ) which allows ready comparison of each of the calculated user workplace preferences ( 119 )(as shown in the example of  FIG.  15    as a bar graph which plots each of the user workplace preferences scores ( 136 ) for “Competiveness” ( 120 ), “Social Responsibility” ( 121 ), “Supportiveness” ( 122 ), “Innovation” ( 123 ), Emphasis on Rewards” ( 124 ), “Performance Orientation” ( 125 ), and “Stability” ( 126 ). 
     Now referring primarily to  FIG.  16   , the program code ( 9 ) can be further executed to concurrently display in the interactive graphical user interface ( 11 ) an occupation fit filter display area ( 139 ) and an occupation fit display area ( 140 ). The program code ( 9 ) can further operate to display in the occupation fit filter display area ( 139 ) a plurality of occupation fit filter icons ( 141 ). 
     In the particular embodiment shown, the occupation fit filter icons ( 141 ) include an occupation zone filter icon ( 142 ) which by click event executes an occupation zone filter ( 143 ) which removes or inserts search control elements ( 144 ) in association with an occupation data retrieval request ( 145 ) which limit retrieval of occupation data ( 146 ) having a corresponding occupation zone identifier ( 147 ) associated with occupations ( 138 ) inside of a bounded geographic area. 
     Similarly, in the particular embodiment shown, the occupation fit filter icons ( 141 ) include an occupation family filter icon ( 148 ) which by click event executes an occupation family filter ( 149 ) which removes or inserts search control elements ( 144 ) in association with an occupation data retrieval request ( 145 ) to limit retrieval of occupation data ( 146 ) to that including a corresponding occupation family identifiers ( 150 ) which typically defines a series of progressively higher, related occupations ( 138 ) distinguished by levels of knowledge, skills, and abilities (competencies) and other factors. 
     Similarly, in the particular embodiment shown, the occupation fit filter icons ( 141 ) include an occupation industry filter icon ( 151 ) which by click event executes an occupation industry filter ( 152 ) which removes or inserts search control elements ( 144 ) in association with an occupation data retrieval request ( 145 ) to limit retrieval of occupation data ( 146 ) to that including a corresponding industry identifiers ( 153 ) which defines occupations ( 138 ) related to a particular a group of businesses that provide a particular product or service. 
     The program code ( 9 ) can be further executed to concurrently display an occupation data retrieval request icon ( 154 ) in the graphical user interface ( 11 ) which by click event initiates an occupation data retrieval request ( 145 ) limited by the occupation fit filters ( 143 )( 149 )( 152 )(or other filters) to retrieve occupation data ( 146 ) stored in a server computer ( 2 ) (shown in the example of  FIG.  16    as “Apply”). 
     Now referring primarily to  FIGS.  1  and  2   , embodiments of the program code ( 9 ) further include a user-occupation matching module ( 155 ) activated upon initiation of an occupation data retrieval request ( 145 ). The user-occupation matching module ( 155 ) when evaluating the occupation fit ( 156 ) (also referred to as “(F p )”) of an user ( 16 ) to a particular occupation ( 138 ), the user attribute category scores ( 52 ) for user values ( 61 ) (“V”) and user interests ( 77 ) (“I”) are considered for a user ( 16 ) (“x”) and an occupation ( 138 ) (“y’). Occupation fit ( 156 ) (F p ) is provided as numerical occupational fit score ( 157 ) in the scale of between 0 to 1, with 0 equating to no occupational fit ( 156 ), and 1 equating to a perfect occupational fit ( 156 ). Occupational fit ( 156 ) (F p ) can be calculated by the user-occupational matching module ( 155 ) by application of the following equation:
 
 F   p =(⅔η I   xy )(⅓η V   xy )
 
     Where η I   xy  (referred to as “an interests fit score ( 158 )”) and η V   xY  (referred to as “a values fit score ( 159 )”) are each determined by application of 
     
       
         
           
             
               η 
               i 
               xy 
             
             ≡ 
             
               
                 
                   
                     ∑ 
                     i 
                   
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   
                     
                       
                         N 
                         i 
                       
                       ⁡ 
                       
                         ( 
                         
                           
                             
                               y 
                               _ 
                             
                             i 
                           
                           - 
                           
                             y 
                             _ 
                           
                         
                         ) 
                       
                     
                     2 
                   
                 
                 
                   
                     ∑ 
                     i 
                   
                   ⁢ 
                   
                     
                       ∑ 
                       α 
                     
                     ⁢ 
                     
                       
                         ( 
                         
                           
                             y 
                             iα 
                           
                           - 
                           
                             y 
                             _ 
                           
                         
                         ) 
                       
                       2 
                     
                   
                 
               
             
           
         
       
     
     Where Σ means “sum of”; and 
     Where N i  is the number of observations of i th  phenomenon, where  i =1, . . . , p in this application N i =2 because there is one set of scores for the user x and one set of scores for the occupation (see the example of Table 5); and 
     Where  y   i  is the average of user interests scores ( 94 ) and the corresponding occupation interest scores ( 160 ) for each of the calculated user interests ( 77 ): “Realistic” ( 78 ), “Investigative” ( 79 ), “Artistic” ( 80 ), “Social” ( 81 ), “Enterprising” ( 82 ), and “Conventional” ( 83 ). For example, if the user interest score ( 94 ) for “Realistic” ( 78 ) is 4.0 and the corresponding occupation interest score ( 160 ) for “Realistic” ( 78 ) is 6.0, then  y   i =5.0, that is, [(4.0+6.0)/2]=5.0; or 
     Where  y   i  is the average of user value scores ( 72 ) and the corresponding occupation values scores ( 161 ) for each of the calculated user values ( 72 ): “Achievement” ( 62 ), “Independence” ( 63 ), “Recognition” ( 64 ), “Relationships” ( 65 ), “Support” ( 66 ), and “Working Conditions” ( 67 ). For example, if the user value score ( 72 ) for “Achievement” ( 62 ) is 4.0 and the corresponding occupation value score ( 161 ) for “Achievement” ( 62 ) is 6.0, then  y   i =5.0, that is, [(4.0+6.0)/2]=5.0; or 
     Where  y   i  is the average of user workplace preferences scores ( 136 ) and the corresponding organization workplace preferences scores ( 136 ) for each of the calculated user workplace preferences scores ( 136 ): “Competiveness” ( 120 ), “Social Responsibility” ( 121 ), “Supportiveness” ( 122 ), “Innovation” ( 123 ), Emphasis on Rewards” ( 124 ), “Performance Orientation” ( 125 ), and “Stability” ( 126 ). Again, if the user workplace preference score ( 136 ) for “Competiveness” ( 120 ) is 4.0 and the corresponding organization workplace preference score ( 163 ) for “Competiveness” ( 120 ) is 6.0, then  y   i =5.0, that is, [(4.0+6.0)/2]=5.0; and 
     Where y iα  refers to the number of entities scored (user ( 16 ), occupation ( 138 ), organization ( 164 ) or the like) for a category (interests ( 77 ), values ( 61 ) or workplace preferences ( 119 ), or the like) (“ i ”) and the number of scored attributes ( 51 ) within a category (“α”). For example, for the category interests ( 77 ) “ i ” applies to user interest scores ( 94 ) plus the occupation interest scores ( 160 ), or user interest scores ( 94 ) plus the organization interest scores ( 217 ), that is “ i ” equals 2.  α  applies to the scored user interests ( 77 ): “Realistic” ( 78 ), “Investigative” ( 79 ), “Artistic” ( 80 ), “Social” ( 81 ), “Enterprising” ( 82 ), and “Conventional” ( 83 ), that is,  α  equals six. 
     As to particular embodiments the plurality of occupations ( 138 ) and corresponding occupation data ( 146 ) can include and correspond to the O*NET OnLine Occupations whether by keyword or O*NET-SOC Code, hereby incorporated by reference herein. 
     As an illustrative example, the occupation fit ( 156 ) determination commences when the user ( 16 ) submits the values assessment instrument ( 60 ) or the an interests assessment instrument ( 76 ) by use of the interactive graphical user interface ( 11 ) including one or more interactive graphical user interface images ( 13 ), as above described, at which point, a set of correlation ratios (η i   xy )( 165 ) are generated comparing the user values scores ( 72 ) and the user interest scores ( 94 ) to the corresponding occupation values score ( 161 ) and the occupation interest scores ( 160 ) associated with one or more occupations ( 138 ) retrievably stored in the computer server ( 2 ). As to particular embodiments, the occupation values score ( 161 ) and occupation interest score ( 160 ) can be the O*NET OnLine Occupations value and interests scores, hereby incorporated by reference herein. 
     In order to generate each one of the set of correlation ratios ( 165 ) to compare the user values scores ( 72 ) and the user interest scores ( 94 ) to the corresponding occupation values score ( 161 ) and the occupation interest scores ( 160 ) associated with one or a plurality of occupations ( 138 ), the a user-occupation matching module ( 155 ) functions to retrieve the occupation values scores ( 161 ) and occupation interest scores ( 160 ) from the server computer ( 2 ). 
     As one illustrative example, the occupation values scores ( 161 ) and occupation interest scores ( 160 ) can be retrieved for the occupation ( 138 ) of Dental Assistant. The occupation values scores ( 161 ) and occupation interest scores ( 160 ) for the occupation ( 138 ) of Dental Assistant are set out in Table 1. 
     
       
         
           
               
               
               
             
               
                   
                 TABLE 1 
               
             
            
               
                   
                   
               
               
                   
                 Values 
                 Interests 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                 Occupation 
                   
                 Occupation  
               
               
                   
                 Psychological 
                 Data 
                 Psychological 
                 Data 
               
               
                   
                 Category Name 
                 Value-Raw 
                 Category Name 
                 Value-Raw 
               
               
                   
                   
               
               
                   
                 Achievement 
                 3.330000 
                 Realistic 
                 5.670000 
               
               
                   
                 Work Conditions 
                 4.170000 
                 Investigative 
                 3.330000 
               
               
                   
                 Recognition 
                 3.000000 
                 Artistic 
                 1.330000 
               
               
                   
                 Relationships 
                 6.000000 
                 Social 
                 4.670000 
               
               
                   
                 Support 
                 5.670000 
                 Enterprising 
                 2.670000 
               
               
                   
                 Independence 
                 3.670000 
                 Conventional 
                 6.000000 
               
               
                   
                   
               
            
           
         
       
     
     The user-occupation matching module ( 155 ) then functions to retrieve the user values scores ( 72 ) and user interest assessment scores ( 94 ) from the server computer ( 2 ). The user values scores ( 72 ) and user interest scores ( 94 ) are set out in Table 2. 
     
       
         
           
               
               
               
             
               
                   
                 TABLE 2 
               
             
            
               
                   
                   
               
               
                   
                 Values 
                 Interests 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                 Candidate  
                   
                 Candidate 
               
               
                   
                 Psychological 
                 Data 
                 Psychological 
                 Data 
               
               
                   
                 Category Name 
                 Value-Raw 
                 Category Name 
                 Value-Raw 
               
               
                   
                   
               
               
                   
                 Achievement 
                 18.000000 
                 Realistic 
                 29.000000 
               
               
                   
                 Work Conditions 
                 10.000000 
                 Investigative 
                 33.000000 
               
               
                   
                 Recognition 
                  6.750000 
                 Artistic 
                 32.000000 
               
               
                   
                 Relationships 
                  8.170000 
                 Social 
                  8.000000 
               
               
                   
                 Support 
                  9.830000 
                 Enterprising 
                 13.000000 
               
               
                   
                 Independence 
                 19.830000 
                 Conventional 
                 24.000000 
               
               
                   
                   
               
            
           
         
       
     
     As to particular embodiments, the occupation values scores ( 161 ) and occupation interest scores ( 160 ) (such as the O*NET values and interests scores) may utilize different scales or the user values scores ( 72 ) or the user interests scores ( 94 ) may use different scales. Accordingly, the user-occupation matching module ( 155 ) can further function to transform the data to provide a common scale ( 166 ) between the scores. As to the embodiment shown in the Figures, the user-occupation matching module ( 155 ) converts occupation interest scores ( 160 ) and occupation values scores ( 161 ) and user interests scores ( 72 ) and user values scores ( 94 ) to a common scale ( 166 )(such as a ten point scale) through use of the following equation: 
     
       
         
           
             
               
                 raw 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 score 
               
               
                 scoring 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 scale 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 maximum 
               
             
             = 
             
               
                 transformed 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 score 
               
               
                 10 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 point 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 scale 
               
             
           
         
       
     
     As such, each occupation score ( 160 ) ( 161 ) is multiplied by 10, and then divided by maximum score obtainable on the common scale ( 166 ). This data transformation yields normalized occupation values scores ( 167 ) and normalized occupation interests scores ( 168 ) for the occupation ( 138 ) of Dental Assistant and normalized user values scores ( 169 ) and normalized user interests scores ( 170 ), as shown in Table 3. 
     
       
         
           
               
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Values 
                 Interests 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 Occupation 
                 User  
                   
                 Occupation 
                 User  
               
               
                 Psychological 
                 Data Value- 
                 Data Value- 
                 Psychological 
                 Data Value- 
                 Data Value- 
               
               
                 Category Name 
                 Normalized 
                 Normalized 
                 Category Name 
                 Normalized 
                 Normalized 
               
               
                   
               
               
                 Achievement 
                 4.757143 
                 8.571429 
                 Realistic 
                 8.100000 
                 7.250000 
               
               
                 Work Conditions 
                 5.957143 
                 4.761905 
                 Investigative 
                 4.757143 
                 8.250000 
               
               
                 Recognition 
                 4.285714 
                 3.214286 
                 Artistic 
                 1.900000 
                 8.000000 
               
               
                 Relationships 
                 8.571429 
                 3.890476 
                 Social 
                 6.671429 
                 2.000000 
               
               
                 Support 
                 8.100000 
                 4.680952 
                 Enterprising 
                 3.814286 
                 3.250000 
               
               
                 Independence 
                 5.242857 
                 9.442857 
                 Conventional 
                 8.571429 
                 6.000000 
               
               
                   
               
            
           
         
       
     
     Following score transformation, the user-occupation matching module ( 155 ) further functions to calculate the set of correlation ratios (η i   xy ) ( 165 ), as above described, for each assessment and retrievably stores the set of correlation ratios ( 165 ) in the server computer ( 2 ). Regardless of the data sets being examined, the process for calculating a correlation ratio takes the same form. 
     For example, in the case of the user values scores ( 72 ) for the user values ( 61 ) of “Achievement” ( 62 ), “Independence” ( 63 ), “Recognition” ( 64 ), “Relationships” ( 65 ), “Support” ( 66 ), and “Working Conditions” ( 67 ), as above described, the following measures can be computed: 
     An overall mean,  y , representing the average of all the user values scores ( 72 ) for user values ( 61 ) being compared; and 
     A set of categorical means, each denoted as  y   i  with i serving as an equation place holder for the specific category, which are the averages of the occupation values scores ( 161 ) and the user values scores ( 72 ) for each category (such as the average of “Achievement” ( 62 )), as above described. 
     For the example of the occupation value scores ( 161 ) for Dental Assistant and the user values scores ( 72 ), the exemplary measures are set forth in Table 4. 
     
       
         
           
               
             
               
                 TABLE 4 
               
             
            
               
                   
               
               
                 Values 
               
            
           
           
               
               
               
               
               
            
               
                   
                   
                   
                 Occupation &amp; 
                 Occupation &amp; 
               
               
                   
                   
                   
                 User Average 
                 User Average 
               
               
                 Psychological 
                 Occupation 
                 User 
                 Data Value By 
                 Data Value 
               
               
                 Category 
                 Data Value- 
                 Data Value- 
                 Category 
                 Overall 
               
               
                 Name 
                 Normalized 
                 Normalized 
                 ( y   i ) 
                 ( y ) 
               
               
                   
               
               
                 Achievement 
                 4.757143 
                 8.571429 
                 6.664286 
                 5.956349 
               
               
                 Work  
                 5.957143 
                 4.761905 
                 5.359524 
                   
               
               
                 Conditions 
                   
                   
                   
                   
               
               
                 Recognition 
                 4.285714 
                 3.214286 
                 3.750000 
                   
               
               
                 Relationships 
                 8.571429 
                 3.890476 
                 6.230952 
                   
               
               
                 Support 
                 8.100000 
                 4.680952 
                 6.390476 
                   
               
               
                 Independence 
                 5.242857 
                 9.442857 
                 7.342857 
               
               
                   
               
            
           
         
       
     
     These values are then used in the following equation: 
     
       
         
           
             
               
                 η 
                 i 
                 xy 
               
               ≡ 
               
                 
                   
                     
                       ∑ 
                       i 
                     
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       
                         
                           N 
                           i 
                         
                         ⁡ 
                         
                           ( 
                           
                             
                               
                                 y 
                                 _ 
                               
                               i 
                             
                             - 
                             
                               y 
                               _ 
                             
                           
                           ) 
                         
                       
                       2 
                     
                   
                   
                     
                       ∑ 
                       i 
                     
                     ⁢ 
                     
                       
                         ∑ 
                         α 
                       
                       ⁢ 
                       
                         
                           ( 
                           
                             
                               y 
                               iα 
                             
                             - 
                             
                               y 
                               _ 
                             
                           
                           ) 
                         
                         2 
                       
                     
                   
                 
               
             
             ⁢ 
             
                 
             
           
         
       
     
     In general, this equation examines the squared difference between the categorical means as they relate to the overall mean, and the squared difference of each individual score as it relates to the overall mean. The square root of the resulting ratio (categorical vs overall over individual vs overall) can be used to describe the degree of similarity between the user values scores ( 72 ) and occupation values scores ( 161 ) with 0 indicating no similarity, and 1 indicating a perfect match. These calculations for the exemplary user ( 16 ) and the exemplary occupation ( 138 ) of Dental Assistant are set out in Table 5. 
     
       
         
           
               
             
               
                 TABLE 5 
               
               
                   
               
               
                 Values 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
               
            
               
                   
                   
                   
                   
                 Numerator- 
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                   
                   
                 Sum of 
                   
                 η i     xy    − 
               
               
                   
                 Psychological 
                   
                   
                 Categorical 
                 η i     xy     2  − 
                 Square 
               
               
                   
                 Category 
                   
                   
                 Difference 
                 Numerator/ 
                 Root of 
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 Name 
                 2( y   i  −  y ) 2   
                 Values 
                 Denominator 
                 η i     xy     2   
               
               
                   
               
               
                 Numerator 
                 Achievement 
                 1.002348 
                 15.823258 
                 0.316424 
                 0.562516 
               
               
                   
                 Work 
                 0.712401 
                   
                   
                   
               
               
                   
                 Conditions 
                   
                   
                   
                   
               
               
                   
                 Recognition 
                 9.735954 
                   
                   
                   
               
               
                   
                 Relationships 
                 0.150814 
                   
                   
                   
               
               
                   
                 Support 
                 0.376932 
                   
                   
                   
               
               
                   
                 Independence 
                 3.844809 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                   
                   
                 Denominator- 
                   
                   
               
               
                   
                   
                   
                   
                 Sum of 
                   
                   
               
               
                   
                   
                   
                   
                 Individual 
                   
                   
               
               
                   
                 Psychological 
                   
                   
                 Score 
                   
                   
               
               
                   
                 Category 
                 (y iα  −  y ) 2   
                 (y iα  −  y ) 2   
                 Difference 
                   
                   
               
               
                   
                 Name 
                 Occupation 
                 User 
                 Values 
               
               
                   
               
               
                 Denominator 
                 Achievement 
                 1.438096 
                 6.838640 
                 50.006523 
                   
                   
               
               
                   
                 Work 
                 0.000001 
                 1.426698 
                   
                   
                   
               
               
                   
                 Conditions 
                   
                   
                   
                   
                   
               
               
                   
                 Recognition 
                 2.791021 
                 7.518912 
                   
                   
                   
               
               
                   
                 Relationships 
                 6.838640 
                 4.267831 
                   
                   
                   
               
               
                   
                 Support 
                 4.595239 
                 1.626637 
                   
                   
                   
               
               
                   
                 Independence 
                 0.509071 
                 12.155738 
               
               
                   
               
            
           
         
       
     
     The user-occupation matching module ( 155 ) further functions to generate a values fit score ( 159 )(for the illustrative example shown above 0.562515) and an interests fit score ( 158 ) (for the illustrative example shown above 0.646781) which was derived by the a user-occupation matching module ( 155 ) in the same fashion. 
     The user-occupation matching module ( 155 ) can further function to utilize the values fit score ( 159 ) and the interests fit score ( 158 ) in the equation:
 
 F   p =(⅔η I   xy )(⅓η V   xy )
 
to determine a user-occupation fit score ( 157 ) (F p ) of 0.618692 for the above illustrative example.
 
     The equation for (F p ) can further include and the user-occupation matching module ( 155 ) can be further executed to apply an interests score allocation factor ( 171 ) within a range of 0 to 1 to the interests fit score ( 158 )(η I   xy ) and allows application of a values score allocation factor ( 172 ) within a range of 0 to 1 to the values fit score ( 159 ) (η I   xy ), wherein the interests score allocation factor ( 171 ) and the values score allocation factor ( 172 ) when summed equal 1. In the illustrative example above, an interest scores allocation factor ( 171 ) equal to about ⅔ was applied to the interests fit score ( 158 ) and a values allocation factor ( 172 ) equal to about ⅓ was applied to the values fit score ( 159 ). Application of an interests scores allocation factor ( 171 ) which is greater than ½ and less than ⅚ has been discovered to generate a user-occupation fit score ( 157 ) which is more predictive of actual user-occupation fit ( 156 ) than previously known. 
     Now referring primarily to  FIG.  16   , as shown in the occupation fit display area ( 140 ), the user-occupation matching module ( 155 ) can transform the results returned as above-described for display by the graphical user interface module ( 11 ) as a list of occupation identifiers ( 173 ) in priority order based upon the user-occupation fit score ( 157 ). Each occupation identifier ( 174 ) can be associated with an occupation fit score indicator ( 175 ) (as shown in the example of  FIG.  16    an alpha fit value ( 176 ) “Strong” and a color code match values ( 177 ) or a numeric match value ( 178 )). 
     Now referring primarily to  FIGS.  17 A and  17 B , as to particular embodiments, by click event a user ( 16 ) can select one of the occupation identifiers ( 174 ) to activate the user-occupation matching module ( 155 ) to retrieve the occupation data ( 146 ) associated with the selected occupation identifier ( 174 ) which can include as an illustrative example an “Alternate Job Title List” ( 179 ) as shown in the example of  FIG.  17 A  or a description of the occupation ( 180 ) as shown in the example of  FIG.  17 B . 
     Now referring primarily to  FIGS.  1  through  3  and  13  through  15   , embodiments of the program code ( 9 ) can further include user-organization match module ( 181 ) which compares the user workplace preferences scores ( 136 ) of a user ( 16 ) to organizational workplace preferences scores ( 163 ) of an organization ( 164 ) (also referred to as “organization culture scores”). Organizational workplace preference scores ( 163 ) can be derived from one or plurality of organization users ( 182 ) of organization ( 164 ) using the interactive graphical user interface ( 11 ) as shown in the example of  FIGS.  3  and  13  through  15    by click event of the workplace preferences category icon ( 116 ) to retrieve and display the workplace preferences assessment instrument ( 118 ). The workplace preferences score calculator ( 135 ) can then generate the workplace preferences scores ( 136 ) for each of a plurality of organizational users ( 182 ) or in selected subpopulation of organization users ( 174 ) (for example, those organization users ( 182 ) in a particular unit of the organization ( 164 ) such as marketing, engineering, accounting, or the like, or those organization users ( 182 ) in the whole of the organization ( 164 ). 
     The user-organization match module ( 181 ) can be executed to calculate user workplace preferences scores ( 136 ) of the user ( 16 ) (“x”) and to calculate organization workplace preferences scores ( 163  (“y”) for each of”: “Competiveness” ( 120 ), “Social Responsibility” ( 121 ), “Supportiveness” ( 122 ), “Innovation” ( 123 ), Emphasis on Rewards” ( 124 ), “Performance Orientation” ( 125 ), and “Stability” ( 126 )”, as above described, and further calculate workplace preferences correlation ratios ( 165 ), as above described, to generate a user-organizational fit score ( 183 ) within a 0-1 scale, with 0 equating to no organization fit, and 1 equating to a perfect organization fit through the following equation:
 
 F   c =η o   xy  
 
     Now referring primarily to  FIG.  18    the program code ( 9 ) can be further executed to concurrently display in the graphical user interface ( 11 ) one or more of: a user pool display area ( 184 ), an occupation display area ( 185 ), an organizational culture display area ( 186 ), and an occupation-organizational culture weighting display area ( 187 ). 
     The occupation display area ( 185 ) can include a list of occupation identifiers ( 173 ) each occupation identifier ( 174 ) correspondingly matched to occupation values score ( 161 ) and occupation interest score ( 160 ), as above described. A particular occupation identifier ( 174 ) can selected by click event from the list of occupation identifiers ( 173 ). 
     The user pool display area ( 184 ) can provide user identifiers or organizational user identifiers (collectively “user identifiers” ( 188 )) corresponding to users ( 16 ) or organization users ( 182 ) having occupation attribute scores ( 53 ) generated by using the one or more attribute assessment instruments ( 57 ), as above described. As to particular embodiments, the user identifiers ( 188 ) can be subdivided into user identifier groups ( 189 ) representing a group of users ( 16 ) ( 182 ) associated with a group identifier ( 190 ) (as shown in the example of  FIG.  18    “Applicants”, “Employees”, “Leaders”, “Sales Group” or the like) which can be selected by click event. 
     The organizational culture display area ( 186 ) allows selection by click event of the organization work preferences scores ( 163 ) representing all organizational users ( 182 ) having organization workplace preferences scores ( 163 ) or representing a subpopulation of organizational users ( 182 ) associated with an organizational group identifier ( 190 ) (for example “Employees”, “Leader”, “Sales Group”). As to particular embodiments, the organizational culture display area ( 186 ) can further include a pre-selected organization scores icon ( 191 ) which by click event activates the user-organization match module ( 181 ) to compare user workplace preferences scores ( 136 ) against pre-selected organization workplace preferences scores ( 192 ) to retrieve a list of user identifiers ( 188 ) having a user-organization fit score ( 183 ) (F c ) which most closely approximates the user-organization fit score ( 183 ) for the pre-selected organization workplace preferences scores ( 192 ). Accordingly, an organization ( 164 ) can employ users ( 16 ) or retain organization users ( 182 ) which align with the desired organization culture rather than the existing organizational culture. 
     The user-organization match module ( 181 ) can be further executed to display an occupation-organization fit weighting display area ( 187 ) which includes an occupation-organizational fit allocator ( 193 ) which by click event allows weighted use of the metrics obtained by the user-occupation match module ( 155 ) and the metrics obtained by the user-organization match module ( 181 ). In the example of  FIG.  18   , the occupation-organization fit allocator ( 193 ) takes the form of a slider ( 194 ) positionable by click event between 100% user-occupation fit score ( 157 ) and 100% user-organizational fit score ( 183 ) to select a weight percent between 0% and 100% for each having a sum equal to 100%. An occupation-organizational fit allocator module ( 195 ) of the program code ( 9 ) can apply selected weighting to the user-occupation fit score ( 157 ) and the user-organization fit score ( 183 ), obtained as above described, to generate a combined user occupation-organizational fit score ( 196 ). 
     The occupation-organizational fit allocator module ( 195 ) can apply the selected weighting to the previously obtained user-occupation fit score ( 157 ) and user-organization fit score ( 183 ) to generate the combined user occupation-organizational fit score ( 196 ) (F pc ). Weighting is defined by percentage of total fit, with each fit to occupation and fit to organization being able to be weighted at a percent in the range of 0% and 100% such that their sum is equal to 100%. For example, a percent value fit to a position F p     a    where a is the weighting for occupation fit, and percent value fit to organizational culture F c     b    where b is the weighting for culture, combined fit F p     a     c     b    is judged on a 0 to 1 scale with 0 equating to no user-organization fit, and 1 equating to a perfect user-organization fit through the following user fit to organization position equation (also referred to as the “fit to position equation):
 
 F   p     a     c     b     ={a ( F   p )}+{ b ( F   c )}
 
     As an illustrative example, the user values fit score (0.562515) (as shown in Table 5), and the user interests fit score (0.646781) can be allocated by the occupation-organizational culture weight allocator module ( 187 ) by the fit to occupation equation, F p =(⅔η I   xy )(⅓η V   xy ), to determine an user-occupation fit score ( 162 ) of 0.618692. This is then combined with the user-organizational fit score ( 175 ) 0.422198, which was derived in the same fashion as those for interest and values, through use of the overall fit to occupation and organizational culture equation F p     a     c     b   ={a(F p )}+{b(F c )} where a and b are the weights assigned to the occupation fit and organization fit respectively. Using a weight of 50% (0.5) for each, the user ( 16 ) demonstrates a combined user occupation-organization fit score ( 196 ) of 0.520445. 
     Now referring primarily to  FIG.  19   , the program code ( 9 ) can be further executed to concurrently display in the graphical user interface ( 11 ) an occupation-organizational culture weight allocator display area ( 197 ) and a user-occupation match display area ( 198 ). 
     As shown in the user-occupation match display area ( 198 ), the occupation-organizational fit allocator module ( 195 ) can transform the results returned for display by the graphical user interface module ( 11 ) as a list of user identifiers ( 188 ) each associated with a combined user occupation-organizational culture fit score ( 196 ), a user-occupation fit score ( 157 ), and an user organizational fit score ( 183 ) (as shown in the example of  FIG.  19    each having an alpha fit value ( 176 ) such as “Strong” and a color code fit values ( 177 ); although a numeric fit value ( 168 ) in the form of the user-occupation fit score ( 157 ), a user-organization fit score ( 157 ) or a combined user occupation-organizational fit score ( 196 ) could also be utilized). 
     As shown in the occupation-organizational culture weight allocator display area ( 197 ), the occupation-organizational culture fit allocator ( 193 ) can take the form of a radial dial ( 199 ) having a slider ( 200 ) positionable by click event between 100% user-occupation fit ( 157 ) and 100% user-organizational fit score ( 196 ), as above described, to select a weight percent between 0-100% for each having a sum equal to 100% (which can be take the form of an occupation percentage indicator ( 201 ) and an organizational culture percentage indicator ( 202 ), as shown in the example of  FIG.  19   ). Adjustment of the occupation-organizational culture weight allocator ( 193 ) by click event can cause the occupation-organizational fit allocator module ( 195 ) to reorder the list of user identifiers ( 188 ) in priority based upon the recalculated combined user occupation-organizational fit score ( 196 ). 
     Again referring primarily to  FIG.  20   , as to particular embodiments, by click event one of the user identifiers ( 188 ) can be selected activate the occupation-organizational fit allocator module ( 195 ) to retrieve user data ( 203 ) associated with the selected user identifier ( 188 ) in the form of a user profile ( 204 ) which can include user assessment information ( 205 ) related to the user value scores ( 72 ), user interest scores ( 94 ), user personality scores ( 114 ), user workplace preferences scores ( 136 ), or the like. 
     Now referring primarily to  FIG.  21   , as to particular embodiments, by click event on a user identifier ( 188 ) the program code ( 9 ) can further function to retrieve and display a fit report ( 206 ) for the user ( 16 ). The fit report ( 206 ) can include selectable user fit icons ( 207 ) including occupation fit icon ( 208 ), organization fit icon ( 209 ), or overall occupation-organization fit icon ( 210 ). By way of example, the occupation fit icons ( 208 ) can further include a user interests fit icon ( 210 ) and a user values fit icon ( 211 ). By click event on a fit icon ( 207 ) a user-occupation assessment report ( 212 ) or a user-organization assessment report ( 213 ) can be retrieved and displayed based on the fit icon ( 207 ) selected. In the illustrative example, selection by click event of a user-interests fit icon ( 211 ) for an occupation ( 138 ) retrieves and displays the user interests ( 77 ), user interests scores ( 94 ) and occupation interests scores ( 160 ) in a columns and row format for ready comparison. As to certain embodiments, color coded fit values ( 177 ) are displayed which by pointer ( 44 ) hover over further display the numeric fit values ( 178 ). As to particular embodiments, the fit report can further include a fit analysis tab ( 214 ). 
     Now referring primarily to  FIG.  22   , by click event of the fit analysis tab ( 214 ), the program code ( 9 ) can further function to generate and display a fit analysis ( 215 ) based upon the user-occupation fit scores ( 157 ) or user-organization fit scores ( 183 ). As to particular embodiments, the fit report ( 206 ) can further include an interview questions tab ( 216 ). 
     Now referring primarily to  FIG.  23   , by click event of the interview questions icon ( 216 ), the program code ( 9 ) can further function to generate and display interview questions ( 217 ). In the illustrative example in which a user interests fit icon ( 210 ) has been selected. The interview questions ( 217 ) will be based on the user interest scores ( 94 ). 
     As can be easily understood from the foregoing, the basic concepts of the present invention may be embodied in a variety of ways. The invention involves numerous and varied embodiments of a computer implemented method for person attribute valuation and matching with occupations and organizations including the best mode. 
     As such, the particular embodiments or elements of the invention disclosed by the description or shown in the figures or tables accompanying this application are not intended to be limiting, but rather exemplary of the numerous and varied embodiments generically encompassed by the invention or equivalents encompassed with respect to any particular element thereof. In addition, the specific description of a single embodiment or element of the invention may not explicitly describe all embodiments or elements possible; many alternatives are implicitly disclosed by the description and figures. 
     It should be understood that each element of an apparatus or each step of a method may be described by an apparatus term or method term. Such terms can be substituted where desired to make explicit the implicitly broad coverage to which this invention is entitled. As but one example, it should be understood that all steps of a method may be disclosed as an action, a means for taking that action, or as an element which causes that action. Similarly, each element of an apparatus may be disclosed as the physical element or the action which that physical element facilitates. As but one example, the disclosure of a “computer” should be understood to encompass disclosure of the act of “computing”—whether explicitly discussed or not—and, conversely, were there effectively disclosure of the act of “computing”, such a disclosure should be understood to encompass disclosure of a “computer” and even a “means for computing.” Such alternative terms for each element or step are to be understood to be explicitly included in the description. 
     In addition, as to each term used it should be understood that unless its utilization in this application is inconsistent with such interpretation, common dictionary definitions should be understood to be included in the description for each term as contained in the Random House Webster&#39;s Unabridged Dictionary, second edition, each definition hereby incorporated by reference. 
     All numeric values herein are assumed to be modified by the term “about”, whether or not explicitly indicated. For the purposes of the present invention, ranges may be expressed as from “about” one particular value to “about” another particular value. When such a range is expressed, another embodiment includes from the one particular value to the other particular value. The recitation of numerical ranges by endpoints includes all the numeric values subsumed within that range. A numerical range of one to five includes for example the numeric values 1, 1.5, 2, 2.75, 3, 3.80, 4, 5, and so forth. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. When a value is expressed as an approximation by use of the antecedent “about,” it will be understood that the particular value forms another embodiment. The term “about” generally refers to a range of numeric values that one of skill in the art would consider equivalent to the recited numeric value or having the same function or result. Similarly, the antecedent “substantially” means largely, but not wholly, the same form, manner or degree and the particular element will have a range of configurations as a person of ordinary skill in the art would consider as having the same function or result. When a particular element is expressed as an approximation by use of the antecedent “substantially,” it will be understood that the particular element forms another embodiment. 
     Moreover, for the purposes of the present invention, the term “a” or “an” entity refers to one or more of that entity unless otherwise limited. As such, the terms “a” or “an”, “one or more” and “at least one” can be used interchangeably herein. 
     Thus, the applicant(s) should be understood to claim at least: i) each of occupational and organizational fit assessment modules or systems herein disclosed and described, ii) the related methods disclosed and described, iii) similar, equivalent, and even implicit variations of each of these devices and methods, iv) those alternative embodiments which accomplish each of the functions shown, disclosed, or described, v) those alternative designs and methods which accomplish each of the functions shown as are implicit to accomplish that which is disclosed and described, vi) each feature, component, and step shown as separate and independent inventions, vii) the applications enhanced by the various systems or components disclosed, viii) the resulting products produced by such systems or components, ix) methods and apparatuses substantially as described hereinbefore and with reference to any of the accompanying examples, x) the various combinations and permutations of each of the previous elements disclosed. 
     The background section of this patent application provides a statement of the field of endeavor to which the invention pertains. This section may also incorporate or contain paraphrasing of certain United States patents, patent applications, publications, or subject matter of the claimed invention useful in relating information, problems, or concerns about the state of technology to which the invention is drawn toward. It is not intended that any United States patent, patent application, publication, statement or other information cited or incorporated herein be interpreted, construed or deemed to be admitted as prior art with respect to the invention. 
     The claims set forth in this specification, if any, are hereby incorporated by reference as part of this description of the invention, and the applicant expressly reserves the right to use all of or a portion of such incorporated content of such claims as additional description to support any of or all of the claims or any element or component thereof, and the applicant further expressly reserves the right to move any portion of or all of the incorporated content of such claims or any element or component thereof from the description into the claims or vice-versa as necessary to define the matter for which protection is sought by this application or by any subsequent application or continuation, division, or continuation-in-part application thereof, or to obtain any benefit of, reduction in fees pursuant to, or to comply with the patent laws, rules, or regulations of any country or treaty, and such content incorporated by reference shall survive during the entire pendency of this application including any subsequent continuation, division, or continuation-in-part application thereof or any reissue or extension thereon. 
     Additionally, the claims set forth in this specification, if any, are further intended to describe the metes and bounds of a limited number of the preferred embodiments of the invention and are not to be construed as the broadest embodiment of the invention or a complete listing of embodiments of the invention that may be claimed. The applicant does not waive any right to develop further claims based upon the description set forth above as a part of any continuation, division, or continuation-in-part, or similar application.