Grant Application for Indigenous Prisoners-Myassignmenthelp.com

Question: Examine about the Health Problems and Social Determinants influencing the Population. Answer: Populace and medical problems The native or indigenous populace of Australia are the countrys local populace. The wellbeing states of the native individuals of the nation are in much more terrible state than the non-local individuals and this postures as an issue for the general national wellbeing principles of Australia. The western colonization in Australia has extraordinarily influenced the wellbeing of the Aboriginal and Torres Strait Islander (ATSI) ladies. The significantly modified financial condition and a move in the natural angles have been the key explanations behind the strength of the aboriginals to become crumbled (Shepherd Phillips, 2016). Among the native ladies, the ones who are presently in jail have much increasingly miserable wellbeing conditions. The soundness of the detained native ladies is the more regrettable among all the racial and ethnic gatherings of the nation. 34 percent of the all out imprisoned populace of the nation is comprised of Australian native ladies. The pace of imprisonme nt across Australia has expanded altogether aside from South Australia. The quantity of detainees in the Australian jails rose by 69 percent in 2016 when contrasted with the quantity of 2015. The local populace of Australia compensates for 2.5 percent of Australias all out populace. A large portion of them live in the Northern Territory and new South grains, as indicated by the Australian Bureau of Statistics (ABS) (Shepherd et al., 2017). As indicated by the Department of Health (DoH), the absolute detained aboriginals establish 27 percent of the all out number of detainees in Australia. There is an obvious variety in the rate development in the quantity of female detainees to be imprisoned throughout the most recent decade when contrasted with the level of the guys for the equivalent. The female detainment rate grew a frightening 42 percent when contrasted with a 24 percent for the guys. Australian native females are the quickest developing populace in the nation. Native females are likewise the most detained populace in the nation with 404 indigenous females to be detained per 100,000 grown-up prisoners in Australia. 90 percent of the imprisoned ladies in the Northern Territory are indigenous. The most extreme medical problem among the detained native ladies is introduction to explicitly transmitted diseases, as the majority of them are inclined to being explicitly dynamic with no assurance because of the limitations and constrainment of jails. Indigenous detained ladies have detailed high quantities of STIs while being confined (Shepherd et al., 2016). The level of native ladies with STIs rose significantly when a time of arraignment. Physical and sexual maltreatment is another serious issue that is looked by the native female detainees. Wild exercises inside the jail is a significant explanation behind the detained females to have blood related infections. Unprotected piercings, getting tattoos, intravenous medication use are generally essential drivers for a high number of native female detainees to have unexpected frailty. In late investigations, emotional well-being of these female native detainees has become a significant issue that should be tended to at the earliest opportunity. Tension, sorrow, schizophrenia and character issue are just probably the most serious emotional wellness issues that are looked by these ladies. The quantity of native female detainees with psychological wellness issues is altogether higher than the male prisoners with emotional well-being issues (Black et al., 2015). PTSD is another significant thing to influence the ladies detainees of indigenous beginning, which regularly lead them towards substance misuse. Right around 60 percent of the detained native females are experiencing psychological well-being issues who additionally are prey to substance misuse. Undertaking portrayal Such poor physical and emotional well-being issues among the native detained females in Australia are far reaching and this is a major issue that should be tended to as quickly as time permits, in any case the nation can't want to keep up a general wellbeing of its residents. Maintainable comprehensive improvement will likewise not be accomplished if this proceeds. Subsequently, there is a critical need to change the state of the female native ladies in jail with emotional wellness issues. It should be comprehended that even the detainees are people and for whatever length of time that they live, they reserve the privilege to live in charge of their own body and psyche (Simpson et al., 2017). it is important to accommodate the emotional wellness of the detainees and the females are to be given more concentration as their lives are consistently in more peril and inclined to ambushes than that of the men (Shepherd Phillips, 2016). No racial or ethnic oppression the native ladies ought to be endured or energized in light of the fact that each individual in the nation are announced to be equivalent in the countrys constitution and it is a criminal offense to hold racial philosophies inside the Commonwealth. The indigenous individuals of Torres waterway have just experienced enough colonization, constrained expulsion from their own territories, digestion, isolation and prejudice. It is the obligation of the Commonwealth to furnish them with the essential human rights and give them the psychological security they merit, regardless of whether they are in jail. It must be considered that the laws of the nation are still not so much for the aboriginals and they face enormous segregation in lawful grounds even at this point. The Torres Strait individuals have consistently seen life from an all encompassing point, where social, enthusiastic and social prosperity are given the same amount of need and significance as physical wellbeing (Baldry Cunneen, 2014). The way that colonization has hindered in the social and public activities of the aboriginals is the significant explanation that ages of the indigenous populace have been dove towards social sadness and nervousness has creeped in. The term restorative home may appear to be a joke as a large portion of the native ladies who are as of now in jail have records of past detainments. Clearly the remedying strategies are not working and should be amended at the earliest opportunity, if the soundness of the ladies are to be improved. Considering these, an arrangement has been formulated that expects to improve the emotional well-being states of the Australian native ladies in jail. A gathering of clinicians have been accumulated who will direct meetings with the native female prisoners. These meetings would be giving the analysts thoughts regarding what do these detainees see as their most overwhelming issues. The analysts would likewise comprehend what are the patterns among these ladies. Explicit circumstances in regards to what are the triggers to set the ladies off and plunge them down a way of psychological sickness would likewise be revealed insight upon (Bradley et al., 2015). The undertaking has been made to be of subjective spellbinding nature that would be investigating the different qualities of the native ladies in Australian detainment facilities and would be progressively disposed towards giving a hypothetical point of view into the issue, instead of just giving measurable information and numerical estimations of the circumstance. Rather, this examination is framed to be considerably more cozy and would be explicitly underlining the realities about what are the main drivers of the psychological issues looked by these females. Targets The examination that has been planned in this venture would give genuinely necessary understanding about the wellbeing states of the local ladies in Australian penitentiaries. Contemporary and as of now existing information and explores exclusively center upon the patterns and what are the most alarming issues that are looked by these ladies. In any case, almost no has been done to comprehend the foundations and mental issues that drive them into discouragement and other intellectually disturbing conditions just as inciting them to maltreatment on substances (Sodhi?Berry et al., 2014). The destinations of the examination have been set in agreement to the underlying thoughts regarding the common issues. These are: To discover what are the issues that are looked by the native females in Australian jails To lead broad studies to have inside and out information about the issues Take interviews with these prisoners to comprehend what are the issues and to investigate what are the underlying drivers of these issues and how may they be activated To make sense of the plausible answers for these issues Spending gauge: An absolute financial plan of $2.500 has been apportioned for the examination work. Reason Apportioned Budget ($) Concerned writing and related books regarding the matter 1,000 Transport for the analysts 500 Fixed 500 Instruments and gear 5000 The spending plan of the exploration has been checked on and endorsed by the board of trustees that is neglecting the whole task and some worldwide and nearby deliberate gatherings have likewise guaranteed additional assets if the advancement of the venture goes as indicated by the underlying plans. That way, a deficiency of assets can be precluded and this would be profoundly valuable for the examination. As the exploration pushes forward, further prerequisites and angles would be seen and more assets will be mentioned varying. Timetable gauge: Fundamental action first week second week third and fourth weeks fifth and sixth weeks seventh and eighth weeks Distinguish the focused on populace of the native female detainees in Australia Usage the successful procedures according to the perceived exploration subjects Screen the actualized technique Changes whenever required Settle the arrangement and methodology The destinations of the undertaking have been set in a manner that would be practical, with the goal that they can be accomplished actually and don't simply remain matters composed on the pape

“Ethnic Notions” Analysis Essay

â€Å"Ethnic Notions† is a chronicled film that takes the watcher through the whole course of American history from the 1820s to the 1980s. The tunes, watching the movies and seeing all the antiques is the thing that makes this film such an integral asset. The film portrays a portion of the terms that were utilized to delineate dark Americans. Well into the twentieth century the â€Å"Mammy†, the â€Å"Coon†, and the â€Å"†Sambo†Ã¢â‚¬  were all terms utilized concerning dark Americans. In 1941 the animation was made and advanced into a significant number of the homes of American culture. In the mid 1900s the picture of the â€Å"Sambo† spread and it turned into a depiction of dark men in film. The Character is languid and flighty that will effortlessly maintain a strategic distance from work to partake in food and move. As the common war drew closer, another character went with the â€Å"Sambo†, the â€Å"Zip Coon†. This character attempted to depict whites that derided the idea of racial uniformity. With these two together, the two of them guarded servitude by saying that blacks can’t handle opportunity. In films the job of the â€Å"†Mammy†Ã¢â‚¬  was a hireling that was characteristically an extremely dim and overwhelming lady that had her needs set to doing whatever her lord or escort wished. â€Å"Mammy† was appeared as a steadfast individual that was defensive over the white family. She was a ground-breaking individual which turned into a steady figure in each picture of the south. It turned out to be difficult to abandon seeing this character in a southern home. This character was additionally a safeguard of bondage. Be that as it may, inside her own family the â€Å"Mammy† is the controlling power which is the direct inverse of the manner in which the family is seen in the public arena. She is appeared as being abiogenetic and ugly. When the slaves became liberated many white individuals said that the previous slaves couldn’t handle being without consistent subjection to their white experts. Society called the liberated blacks beasts, and the expanding open dread of them gave them the epithet of â€Å"black menace.† Once movie was created in the twentieth century the pictures and the delineation of dark Americans didn’t change by any means. The main contrast currently is the loathe is presently on film. Blacks started to enter theater and they utilized it as a positive development to escape the south and start another life withâ opportunities. Through the 1940s the blackface became disposed of however its picture left its blemish on society. Before long kid's shows turned into the voice for bigotry. Along these lines when any savagery or abuse were happening it would be engaging and comical. The kid's shows had the ability to impact youthful personalities to consider generalizations to be being engaging by making references to dark Americans being savages. Besides the main thing that tamed dark Americans was subjugation. The legend says without the whites authority over the blacks, their whole race would end up being simply savages. â€Å"Ethnic Notions† is an inside and out gander at the foundations of African American bigotry and generalizations. The film experiences 150 years of bigotry and disdain towards dark Americans, and the pictures that were spread all through society that delineated African Americans to being lethargic and imprudent. Additionally without bondage to hold them in line, fantasies state that they would depend on savage conduct.

Best Uses of Big Data in Recruiting

Best Uses of Big Data in Recruiting Big Data â€" the collection of larger than average datasets that require unconventional storage, processing, and analysis methods, has revolutionized nearly every field of business, from marketing to manufacturing. Big Data can provide those firms that develop the infrastructure to analyze and act on the patterns and insights contained in these datasets, with a source of competitive advantage in any industry.This infrastructure includes the technology to aggregate, process, and analyze various datasets, and the personnel to perform these operations, which marketing research firm Gartner estimates will be a $232 billion dollar industry by 2016.As more and more firms invest in Big Data infrastructure and integrate it into their existing internal operations, such personnel are in high demand these days. Firms often find them with the help of Big Data-driven recruiting procedures. Indeed, Big Data has transformed the world of recruiting; and it may help you find the talent you need, in e ach area of your business.Big Data, or people analytics, as it is known when applied to recruiting, provides recruiters with more data to analyze. Social media networks have become the first stop for many recruiters after receipt of a resume. However, people analytics encompasses more than just social media data mining. Indeed, it encompasses even more than just back-end software or personnel. People analytics is also an orientation â€" an attempt to create a complete picture of a candidate long before they step foot in an office for an interview. An applicants entire online presence, their use of a firms recruiting database, their customer or non-customer status, their political affiliations, their smoking preferences, and other characteristics can all taken into consideration in this era of Big Data. © Shutterstock.com | Rawpixel.comIn this article, we will cover 1) the benefits of recruiting using Big Data; 2) recruiting using Big Data; 3) the risks of using Big Data for recruiting; 4) the future of hiring with Big Data; and 5) a case study of a business using Big Data.BENEFITS OF RECRUITING USING BIG DATAThe people analytics approach has tremendous advantages for recruiters. The proliferation of available information about candidates has made it possible for recruiters and human resources professionals to match an employee’s professional and personal fit with their firm more closely to the firm’s opening and corporate culture respectively. People analytics’ tools and techniques allow firms to develop a much more complete profile of a candidate â€" far beyond a one-page cover letter and accompanying resume.People analytics allows firms to move away from hiring based on subjective factors that may have very little to do with an employee’s chances of success at that parti cular firm. The Big Data approach involves first determining what existing factors lead to employee success and retention, and hiring candidates who fall within those parameters. This approach makes it easier for recruiters and managers to justify new hires as well. And it works. Xerox recently used algorithm-driven recruiting techniques to reduce the attrition in its call centers by 20%.Further, analyses of one’s internal HR database, its strategic sales plan, and its accounts receivable, can yield insights about where a firm needs to hire to stay on top of existing orders. This insight allows firms to recruit proactively, rather than when they face a talent shortfall. Hiring proactively allows firms to spend the time necessary to select the right candidate, and avoid paying a premium for talent in moments of extreme organizational need. It also allows firms to develop strategic recruitment plans that incorporate a firm’s broader hiring goals, such as building a diverse workfor ce.People analytics can reduce your cost per hire, and your average time needed to fill open positions by making the recruiting process more efficient. Lastly, hiring using people analytics can align your compensation packages more closely with real market averages, by conducting analyses of publicly available salary information.RECRUITING USING BIG DATABig Data has given rise to a number of recruiting techniques designed to make recruiting efforts more precise and accurate. While these techniques predate the rise of Big Data, the explosion of available information has led to the development of algorithm-driven recruiting software solutions (as well as firms that specialize in algorithm-driven recruiting); and helped refine the tools and techniques used specifically for recruiting. These tools and techniques include data mining, keyword filtering, and testing.Data miningData mining is a technique used by firms to aggregate data for a variety of different business purposes, including recruiting. Data mining can be used to analyze the internal data created by high-performing and/or longstanding candidates to search for insights into their performance and/or longevity. Data-driven firms like IBM, along with standalone data analysis firms like the California-based Cataphora, specialize in such statistical analyses, which can be used for internal recruiting and/or retention. By analyzing from where successful candidates have been hired can simplify the recruiting process as well. For example, a firm whose internal analyses have revealed that 49% of their top performers had their initial contact with a recruiter from Viadeo, may lead the firm to reduce advertising on LinkedIn, and instead ramp up recruitment efforts on the French social networking site.Recruiters and human resources professional can also combine data mining with predictive analytics â€" the use of statistical methods and techniques to forecast the probability of a likelihood occurrence using histori cal data, to generate predictions about a candidate’s likely tenure with the firm should they be hired. These insights can also be used to provide parameters for the recruiting of external candidates.Data mining, or as some recruiters call it “talent mining” can be done manually or automatically online. Individual recruiters and/or software can search online resume databases (internal or external), professional social network profiles, or other websites of interest for personnel who might be a match for an opening.Social networks, in particular, capture significant information about an individual. Recruiters can determine not only whether a candidate might be a good fit for the culture of the firm, but also whether they might be successful there, by assessing this information against internal profiles of high performing candidates. For example, a firm’s highest performers may spend a small amount of time on a single social network. A candidate who spends considerable time on multiple social networks might raise some flags. Alternatively, a social network might indicate that the candidate is engaged in activities that might impair their productivity, such as excessive drinking or high-risk hobbies, such as extreme sports. These insights can be helpful to the diligent recruiter.Keyword filteringUsing desired skills and other characteristics as keywords, recruiters can run searches in popular search engines, on professional and non-professional search engines, in public or private online communities, and on other online properties. This can yield promising leads, who recruiters can contact for an informational or formal interview.Keyword filtering is also helpful when screening out applicants who have applied for a position through a web-based talent management application (either proprietary or from a third-party recruiter). Recruiting software automatically scans submitted resumes and cover letters for specific keywords, rejecting those without them, an d returning to recruiters only the candidates who fit the job description on paper.TestingMore and more, testing is used in the hiring process. Usually, pre-screened applicants are invited to take a skills test, a personality test, or both. Skills tests are used to authenticate the skills listed in one’s job application, but also can be used to test those not listed, such as soft skills. Personality tests are used to assess a candidate’s fit with the firm’s culture, as well as soft skills. Personality tests have been around for a long time, but the combination of computer-assisted testing, and data-driven approached to psychology, make these tests much more sophisticated and precise.Increasingly, both skills and personality tests are assessed against internal analyses of high performing employees. For example, an advertising firm may find success with candidates who work well in a team and possess a high degree of digital fluency, regardless of the job opening. They may in tur n offer measure all candidates for an opening against skills and personality tests they mandate during the hiring process.It is not uncommon for candidates for senior positions in all industries (and even some junior level positions in industries such as finance) to be given one or multiple, skills tests, and a personality test, during multiple interview rounds. These tests provide hiring managers with more data points, alongside the job application, the interview(s), online data, and other publicly available information, against which to measure candidates. RISKS OF USING BIG DATA FOR RECRUITINGBig Data may yield tremendous potential for recruiting, and indeed, for many firms, some big results. However, there are risks to using algorithm-driven recruiting tactics that can lead to some substantial consequences. These risks stem from overreliance on algorithm-driven recruiting. People analytics should, ideally, supplant human recruiting efforts, rather than supplant them.Incorrect fo recasting assumptionsUsing profiles developed by analyses of internal data can yield promising candidates. Nevertheless, this assumes that the analyses provide accurate insights into what it takes to perform at the firm. The best analyses have a degree of uncertainty, and employee performance standards constantly change along with the demands of the markets. Historical performance is no guarantee of future performance. Further, Big Data is notoriously messy. It is critical that you invest in either a data-driven recruiting firm or the personnel to analyze recruitment-relevant data. Your HR people, even the best intentioned, may not be able to properly analyze multiple datasets to generate actionable recruitment insights. You will need statisticians.It is also very important to understand that the models predicting candidate success are based on how strongly a particular candidate’s characteristics are correlated with the characteristics of a hypothetical high performer employed by the firm. Correlation does not imply causality, which means, in this case, that just because a candidate is identical to the hypothetical performer on all levels those data do not mean that he or she will definitely succeed. If you approach people analytics expecting to find set parameters for candidates that will always result in success, you are likely to be disappointed.Moreover, assessing candidates individually, pre-employment (and even post-hire) rarely yields insights into what said individuals can contribute to a team. For example, designing an algorithm that predicts whether an individual whose performance may be average but who may provide rousing pep talks to team members outside of work, is challenging at best.It should be noted that privacy is also a big concern, particularly when it comes to internal data gathering. Employees, using resources belonging to an employer, should expect a certain amount of data gathering. But how much is too much? At what point does data-g athering feel invasive and undermine productivity â€" the very thing the firm seeks to measure?Human beings design the recruitment algorithms so, in addition to the possibility of human error in the design and/or implementation, of the algorithms, there is the likelihood of bias, especially when it comes to less objective measures of success. People tend to associate with people like themselves. Using algorithms that use historical data to predict employee performance as hiring parameters may yield candidates who are similar to existing candidates, but neglect those who are different enough to innovate. As innovation is a key source of not just competitive advantage, but ability to adapt to market dynamics, over time, a homogenous staff may hurt your firm.Violations of equal opportunity lawsHomogenous employees may hurt your firm in ways other than reduced innovation. Recruiters must make sure that their hiring algorithms do not systematically exclude classes of protected employees. The fact that an algorithm repeatedly returned a single ethnic group or gender is not an excuse in the eyes of the U.S. Equal Employment Opportunity Commission, and other foreign counterparts. Recruiters must take pains to ensure that the algorithm takes a country’s diversity laws, both through automatic and manual review of the candidates returned by software at every stage of the interview process. Failure to do so can be time-consuming and costly in the case of either resulting civil litigation, or damage to your firm’s brand.Even entire industries are not immune from the need to vary their recruiting approaches. In August of 2014, a flurry of reports highlighted the lack of diversity in Silicon Valley. This was at least partially attributed to algorithm-driven recruiting practices.FUTURE OF HIRING AND BIG DATADespite the risks, algorithm-driven approaches to recruiting are here to stay. Big Data has accelerated the rate of advancement in machine learning. Machine learning i s the design and study of learning algorithms that, essentially, help a computer process and understand data better. As the field of machine learning advances, so too will the sophistication and accuracy of algorithm-based recruitment tools.Moreover, the cost of hiring the wrong candidate is high. Training, salary and benefits, and search related costs just scratch the surface if the new hire’s mistakes cost revenue. The potential benefit of algorithm-driven recruitment methods, in the estimation of most firms, outweighs the growing pains associated with new approaches. Moreover, algorithm-driven approaches already have worked well for a number of firms.CASE STUDY © Wikimedia commons | GoogleCase in point: Google. It is expected that a firm as data-driven as Google would be a pioneer in data-driven approaches to recruiting. Google has dedicated resources to building a hiring algorithm, which predicts a candidate’s probability for success if hired. They also developed a separate algorithm designed to backstop its initial screening of candidate resumes, which indicated that its primary algorithm had missed 1.5% percent of the time.Their dedication to research-driven approach also informed their application process. After much research, they determined that four interviews provided the maximum amount of insight. They make considerable use of behavioral interviews. Further, they employed group hiring to reduce bias dramatically in hiring decisions.Google has also developed retention algorithm, using predictive modeling methods that predict the probability of success of employees, post-hire, and applying them to the dynamic data that is reflecti ve of a growing and changing workforce. This has informed their hiring practices by allowing Google to refine the parameters of their hiring algorithm. They have also used analytics to increase the hiring of underrepresented groups, such as women.As a result, Google has been able to fill vacancies rapidly, and enjoyed both low turnover and a reputation for being very selective, enhancing its prestige as a top employer brand for years.Big Data for Recruitment | SourceIn London 2013

Best Uses of Big Data in Recruiting

Best Uses of Big Data in Recruiting Big Data â€" the collection of larger than average datasets that require unconventional storage, processing, and analysis methods, has revolutionized nearly every field of business, from marketing to manufacturing. Big Data can provide those firms that develop the infrastructure to analyze and act on the patterns and insights contained in these datasets, with a source of competitive advantage in any industry.This infrastructure includes the technology to aggregate, process, and analyze various datasets, and the personnel to perform these operations, which marketing research firm Gartner estimates will be a $232 billion dollar industry by 2016.As more and more firms invest in Big Data infrastructure and integrate it into their existing internal operations, such personnel are in high demand these days. Firms often find them with the help of Big Data-driven recruiting procedures. Indeed, Big Data has transformed the world of recruiting; and it may help you find the talent you need, in e ach area of your business.Big Data, or people analytics, as it is known when applied to recruiting, provides recruiters with more data to analyze. Social media networks have become the first stop for many recruiters after receipt of a resume. However, people analytics encompasses more than just social media data mining. Indeed, it encompasses even more than just back-end software or personnel. People analytics is also an orientation â€" an attempt to create a complete picture of a candidate long before they step foot in an office for an interview. An applicants entire online presence, their use of a firms recruiting database, their customer or non-customer status, their political affiliations, their smoking preferences, and other characteristics can all taken into consideration in this era of Big Data. © Shutterstock.com | Rawpixel.comIn this article, we will cover 1) the benefits of recruiting using Big Data; 2) recruiting using Big Data; 3) the risks of using Big Data for recruiting; 4) the future of hiring with Big Data; and 5) a case study of a business using Big Data.BENEFITS OF RECRUITING USING BIG DATAThe people analytics approach has tremendous advantages for recruiters. The proliferation of available information about candidates has made it possible for recruiters and human resources professionals to match an employee’s professional and personal fit with their firm more closely to the firm’s opening and corporate culture respectively. People analytics’ tools and techniques allow firms to develop a much more complete profile of a candidate â€" far beyond a one-page cover letter and accompanying resume.People analytics allows firms to move away from hiring based on subjective factors that may have very little to do with an employee’s chances of success at that parti cular firm. The Big Data approach involves first determining what existing factors lead to employee success and retention, and hiring candidates who fall within those parameters. This approach makes it easier for recruiters and managers to justify new hires as well. And it works. Xerox recently used algorithm-driven recruiting techniques to reduce the attrition in its call centers by 20%.Further, analyses of one’s internal HR database, its strategic sales plan, and its accounts receivable, can yield insights about where a firm needs to hire to stay on top of existing orders. This insight allows firms to recruit proactively, rather than when they face a talent shortfall. Hiring proactively allows firms to spend the time necessary to select the right candidate, and avoid paying a premium for talent in moments of extreme organizational need. It also allows firms to develop strategic recruitment plans that incorporate a firm’s broader hiring goals, such as building a diverse workfor ce.People analytics can reduce your cost per hire, and your average time needed to fill open positions by making the recruiting process more efficient. Lastly, hiring using people analytics can align your compensation packages more closely with real market averages, by conducting analyses of publicly available salary information.RECRUITING USING BIG DATABig Data has given rise to a number of recruiting techniques designed to make recruiting efforts more precise and accurate. While these techniques predate the rise of Big Data, the explosion of available information has led to the development of algorithm-driven recruiting software solutions (as well as firms that specialize in algorithm-driven recruiting); and helped refine the tools and techniques used specifically for recruiting. These tools and techniques include data mining, keyword filtering, and testing.Data miningData mining is a technique used by firms to aggregate data for a variety of different business purposes, including recruiting. Data mining can be used to analyze the internal data created by high-performing and/or longstanding candidates to search for insights into their performance and/or longevity. Data-driven firms like IBM, along with standalone data analysis firms like the California-based Cataphora, specialize in such statistical analyses, which can be used for internal recruiting and/or retention. By analyzing from where successful candidates have been hired can simplify the recruiting process as well. For example, a firm whose internal analyses have revealed that 49% of their top performers had their initial contact with a recruiter from Viadeo, may lead the firm to reduce advertising on LinkedIn, and instead ramp up recruitment efforts on the French social networking site.Recruiters and human resources professional can also combine data mining with predictive analytics â€" the use of statistical methods and techniques to forecast the probability of a likelihood occurrence using histori cal data, to generate predictions about a candidate’s likely tenure with the firm should they be hired. These insights can also be used to provide parameters for the recruiting of external candidates.Data mining, or as some recruiters call it “talent mining” can be done manually or automatically online. Individual recruiters and/or software can search online resume databases (internal or external), professional social network profiles, or other websites of interest for personnel who might be a match for an opening.Social networks, in particular, capture significant information about an individual. Recruiters can determine not only whether a candidate might be a good fit for the culture of the firm, but also whether they might be successful there, by assessing this information against internal profiles of high performing candidates. For example, a firm’s highest performers may spend a small amount of time on a single social network. A candidate who spends considerable time on multiple social networks might raise some flags. Alternatively, a social network might indicate that the candidate is engaged in activities that might impair their productivity, such as excessive drinking or high-risk hobbies, such as extreme sports. These insights can be helpful to the diligent recruiter.Keyword filteringUsing desired skills and other characteristics as keywords, recruiters can run searches in popular search engines, on professional and non-professional search engines, in public or private online communities, and on other online properties. This can yield promising leads, who recruiters can contact for an informational or formal interview.Keyword filtering is also helpful when screening out applicants who have applied for a position through a web-based talent management application (either proprietary or from a third-party recruiter). Recruiting software automatically scans submitted resumes and cover letters for specific keywords, rejecting those without them, an d returning to recruiters only the candidates who fit the job description on paper.TestingMore and more, testing is used in the hiring process. Usually, pre-screened applicants are invited to take a skills test, a personality test, or both. Skills tests are used to authenticate the skills listed in one’s job application, but also can be used to test those not listed, such as soft skills. Personality tests are used to assess a candidate’s fit with the firm’s culture, as well as soft skills. Personality tests have been around for a long time, but the combination of computer-assisted testing, and data-driven approached to psychology, make these tests much more sophisticated and precise.Increasingly, both skills and personality tests are assessed against internal analyses of high performing employees. For example, an advertising firm may find success with candidates who work well in a team and possess a high degree of digital fluency, regardless of the job opening. They may in tur n offer measure all candidates for an opening against skills and personality tests they mandate during the hiring process.It is not uncommon for candidates for senior positions in all industries (and even some junior level positions in industries such as finance) to be given one or multiple, skills tests, and a personality test, during multiple interview rounds. These tests provide hiring managers with more data points, alongside the job application, the interview(s), online data, and other publicly available information, against which to measure candidates. RISKS OF USING BIG DATA FOR RECRUITINGBig Data may yield tremendous potential for recruiting, and indeed, for many firms, some big results. However, there are risks to using algorithm-driven recruiting tactics that can lead to some substantial consequences. These risks stem from overreliance on algorithm-driven recruiting. People analytics should, ideally, supplant human recruiting efforts, rather than supplant them.Incorrect fo recasting assumptionsUsing profiles developed by analyses of internal data can yield promising candidates. Nevertheless, this assumes that the analyses provide accurate insights into what it takes to perform at the firm. The best analyses have a degree of uncertainty, and employee performance standards constantly change along with the demands of the markets. Historical performance is no guarantee of future performance. Further, Big Data is notoriously messy. It is critical that you invest in either a data-driven recruiting firm or the personnel to analyze recruitment-relevant data. Your HR people, even the best intentioned, may not be able to properly analyze multiple datasets to generate actionable recruitment insights. You will need statisticians.It is also very important to understand that the models predicting candidate success are based on how strongly a particular candidate’s characteristics are correlated with the characteristics of a hypothetical high performer employed by the firm. Correlation does not imply causality, which means, in this case, that just because a candidate is identical to the hypothetical performer on all levels those data do not mean that he or she will definitely succeed. If you approach people analytics expecting to find set parameters for candidates that will always result in success, you are likely to be disappointed.Moreover, assessing candidates individually, pre-employment (and even post-hire) rarely yields insights into what said individuals can contribute to a team. For example, designing an algorithm that predicts whether an individual whose performance may be average but who may provide rousing pep talks to team members outside of work, is challenging at best.It should be noted that privacy is also a big concern, particularly when it comes to internal data gathering. Employees, using resources belonging to an employer, should expect a certain amount of data gathering. But how much is too much? At what point does data-g athering feel invasive and undermine productivity â€" the very thing the firm seeks to measure?Human beings design the recruitment algorithms so, in addition to the possibility of human error in the design and/or implementation, of the algorithms, there is the likelihood of bias, especially when it comes to less objective measures of success. People tend to associate with people like themselves. Using algorithms that use historical data to predict employee performance as hiring parameters may yield candidates who are similar to existing candidates, but neglect those who are different enough to innovate. As innovation is a key source of not just competitive advantage, but ability to adapt to market dynamics, over time, a homogenous staff may hurt your firm.Violations of equal opportunity lawsHomogenous employees may hurt your firm in ways other than reduced innovation. Recruiters must make sure that their hiring algorithms do not systematically exclude classes of protected employees. The fact that an algorithm repeatedly returned a single ethnic group or gender is not an excuse in the eyes of the U.S. Equal Employment Opportunity Commission, and other foreign counterparts. Recruiters must take pains to ensure that the algorithm takes a country’s diversity laws, both through automatic and manual review of the candidates returned by software at every stage of the interview process. Failure to do so can be time-consuming and costly in the case of either resulting civil litigation, or damage to your firm’s brand.Even entire industries are not immune from the need to vary their recruiting approaches. In August of 2014, a flurry of reports highlighted the lack of diversity in Silicon Valley. This was at least partially attributed to algorithm-driven recruiting practices.FUTURE OF HIRING AND BIG DATADespite the risks, algorithm-driven approaches to recruiting are here to stay. Big Data has accelerated the rate of advancement in machine learning. Machine learning i s the design and study of learning algorithms that, essentially, help a computer process and understand data better. As the field of machine learning advances, so too will the sophistication and accuracy of algorithm-based recruitment tools.Moreover, the cost of hiring the wrong candidate is high. Training, salary and benefits, and search related costs just scratch the surface if the new hire’s mistakes cost revenue. The potential benefit of algorithm-driven recruitment methods, in the estimation of most firms, outweighs the growing pains associated with new approaches. Moreover, algorithm-driven approaches already have worked well for a number of firms.CASE STUDY © Wikimedia commons | GoogleCase in point: Google. It is expected that a firm as data-driven as Google would be a pioneer in data-driven approaches to recruiting. Google has dedicated resources to building a hiring algorithm, which predicts a candidate’s probability for success if hired. They also developed a separate algorithm designed to backstop its initial screening of candidate resumes, which indicated that its primary algorithm had missed 1.5% percent of the time.Their dedication to research-driven approach also informed their application process. After much research, they determined that four interviews provided the maximum amount of insight. They make considerable use of behavioral interviews. Further, they employed group hiring to reduce bias dramatically in hiring decisions.Google has also developed retention algorithm, using predictive modeling methods that predict the probability of success of employees, post-hire, and applying them to the dynamic data that is reflecti ve of a growing and changing workforce. This has informed their hiring practices by allowing Google to refine the parameters of their hiring algorithm. They have also used analytics to increase the hiring of underrepresented groups, such as women.As a result, Google has been able to fill vacancies rapidly, and enjoyed both low turnover and a reputation for being very selective, enhancing its prestige as a top employer brand for years.Big Data for Recruitment | SourceIn London 2013