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Results A methodological tool was developed which integrate 40 OH indicators distributed by the four fields of the conceptual framework of "health indicators of sustainable jobs" Table 1. Proportion of workers covered by OHS Services 3. Frequency of occasional health exams 5. Ratio of occupational physicians 6. Ratio of occupational nurses 7. Distribution of LUs by workplace health promotion 8. Proportion of workers covered by workplace health promotion 9. Proportion of workers covered by actions of OHS information Proportion of workers covered by OHS training actions Health risks at the workplace: Proportion of workplaces in public and private sectors formal and informal that comply with basic national occupational safety and health standards by economic sector.

Distribution of LUs by occupational risks identification Distribution of LUs by occupational risk prevention programme Distribution of LUs by physical hazard identification Occupational exposure by physical hazard Distribution of LUs by chemical hazard identification Occupational exposure by chemical hazard Distribution of LUs by biological hazard identification Occupational exposure by biological hazard Distribution of LUs by hazard identification related to the activity Occupational exposure by hazard related to the activity Distribution of LUs by other hazard identification Occupational exposure by other hazard Health effects - occupational deaths, injuries and disabilities Occupational injury rate fatal disaggregated by gender, occupation, employment type formal and informal , and economic sector.

Incidence rate of accidents at work Incidence rate of fatal accidents at work Frequency rate of accidents at work Severity rate of accidents at work Absenteeism rate by accidents at work Incidence rate by occupational disease s reported Social determinants of workers' health: Health indicators for monitoring the health impacts of sustainable development policies regarding jobs should be used in conjunction with the set of indicators for measuring decent work.

Distribution of workers by level of professional qualification degree Distribution of workers by type of employment contract Distribution of workers by working time arrangements Distribution of workers by the organization of working time Distribution of LUs by query actions for workers Proportion of workers covered by query actions Average remunerations of workers Conclusions The diversity of indicators used in this study were selected from the OHS indicator systems, as referred in the text.

Helsinquia: Finnish Institute of Occupational Health; Geneva: World Health Organization; Beijing - China: World Health Organization; Compromisso para o Crescimento Verde. United Nations Environment Programme; International Labour Office; What policies for a green economy that works for social progress?

Labour Res. European Commission; Stakeholders' perception of the possible implications of "green jobs" for health and safety at work in Italy. Ind Health ; 53 : Green jobs for the disadvantaged: an analysis of government policies in British Columbia. J Environ Plan Manage ; 59 : Luxembourg: Office of the European Union; Geneva: International Labour Organization; Fundamental principles of occupational health and safety. Geneva: International Labour Office; United Nations; Measuring employment precariousness in the European working conditions survey: The social distribution in Europe.

Work ; 49 : Indicators of healthy work environments - A systematic review. Work ; 41 : Epidemiological and performance indicators for occupational health services: a feasibility study in Belgium. Scottish Government; We believe that the way employers speak to, and interact digitally with their candidates has a big impact on their employer brand, on their talent pipeline, and eventually on their success. In the world of consumer products, all kinds of studies on behaviour and preferences are done to sell more.

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The cor- rection involves reweighting the sample to reflect the differences in the sampling probabilities of sample members. Such a weighting scheme wouIcl give greater weight to offender types who are uncler- represented in a sample and less weight to those who are overrepresented. General population and offender-basec! General population samples, which include offenders and nonoffend- ers, are more appropriate for estimating participation rates. The undercount of high-rate offenders in such samples will understate participation, but this bias is not likely to be substantial because of the small numbers of high-rate offenders among total offenders.

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However, general population samples are inefficient for es- timating frequency rates of active offend- ers because of the low yield of active offenders in such samples. The ineffi- ciency is aggravated by the underrepre- sentation of high-rate offenders in those samples.

Samples of arrestees or inmates are better suites! Thus, all such research is inherently longitudinal. There are many ways in which such longitudinal research can be pursued. The most obvious wouIc! The most important disadvantage of this ap- proach is the Tong time required to develop results. Thus, for exam- ple, a cohort that reached maturity before the sharp rise in drug use ofthe late s would yield no information on the influ- ence of drug use on involvement in other criminal activity. A different approach to longitudinal re- search is a retrospective Tongituclinal de- sign.

This approach avoids the Tong delay associated with the prospective stu ly by defining a cohort and reconstructing its prior criminal involvement. In the absence of longitudinal data, annual cross-sectional data can be used to synthesize a cohort by examining varia- tions across age within a year as a proxy for longitudinal age variations of a cohort. However, the two may not be equivalent. If there are important cohort effects, then those cohort effects will be confounded with age effects in a synthesized cohort. If there is a positive association between career length and A, for example, then a cross-section cohort will display a larger average A and more high-rate offenders than a natural cohort; a negative associa- tion will lead to the opposite effects.

Fur- thermore, a cross-section design pre- cludes examining temporal sequences within individuals, which is a main fea- ture of longitudinal cohort designs. A major problem with single-cohort de- signs is that age effects are inextricably confouncled with historical effects. Thus, a cohort that happened to reach the high- crime ages of the mid-teens at a time of consi lerable social turmoil wouIcl display an amplified age effect in involvement in crime compared with another cohort that.

Analysis of a single cohort -C would not be able to isolate these effects. One way to overcome this problem is by drawing multiple cohorts and obtaining longitudinal data on them. Because of resiclential migration, how- ever, the members of the cross-section sample will cliffer from the birth cohorts within the jurisdiction studied. Also, if the cross-section sample is drawn from an arrestee population or some other of- fencler sample , then the older members of the cross-section sample wit! The relative strengths ant!

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For each of these periods, prospective longitudinal data on criminal activity and other related events should be collected on cohort members. Those data can and shouIc! In some cases, there are interactions among various dimensions, which result in pos- sible distortions in the separate estimates for each dimension.

The possibility of career termination cLuring a follow-up pe- riocI, for example, distorts estimates of A for offenders who remain active, since some offenders will ens! If A is calculated by assuming that all offend- ers are active throughout the follow-up period, failure to account for this short- ened duration for some offenders will result in a downward! For example, such studies include analyses of trencis in offense seriousness or in A as offenders age or accumulate arrests. When such trends are established they are often at- tributec!

Another interpretation of observed trencis that is rarely invoked, however, involves none of these causal explanations but derives from offender heterogeneity.

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Uncler this interpretation, different offender groups wilt display clif- ferential persistence in their criminal ca- reers. In such a situation, the more per- sistent groups and their characteristics increasingly dominate samples of offend- ers who are observer! To the extent that of- fencler heterogeneity is a factor in gener- ating the observed trends and is not ade- quately controllecl in the analysis ofthem, the changing composition of the offender population over the course of careers will be incorrectly interpreted as changes in the behavior of offenders.

Measurements of career dimensions of- ten slider across studies and are some- times characterizes] as presenting con- flicting information. In many cases, however, the differences in measure- ments are attributable to differences in. For example, participation rates wflT be higher for all offenses than for violent offenses, for cumulative lifetime partici- pation BL than for participation by age 18 Bit , and for samples of mates alone than for samples of mates and females.

Therefore, any reporting of criminal ca- reer measurements must indicate the ba- sis of the measurements. Variations in exposure time can also affect measurements of criminal career dimensions. For example, if an individual initiates or terminates a career midway through an observation period, then the estimate of his offending frequency, when distributed over the entire period, would be only halfhis true rate cluring his active periocl.

A similar distortion could occur in analyzing the effects of covari- ates on criminal career dimensions. Con- sider, for example, the relationships be- tween precursor behaviors, such as alcohol or marijuana use, ant! Thus, even if both sub- stances had the same influence in initiat- ing delinquent careers, more of the alco- hoT users would have had the opportunity to begin offending within the observation period than would marijuana users. Iso- lating the relative influence of these two covariates on participation requires ade- quate controls for the differences in times at risk Robins and Wish, Identifying the covariates of criminal careers is especially important both for improving theory on the causes of incli- vidual criminality and for distinguishing among offenders for various policy pur- poses.

The proportional hazards method! Its primary application in criminology has been to data on time to recidivism Barton and Turnbull, By relying on time to a first recidivist event as the clependent variable, however, these models cannot distinguish the separate effects of covari- ate s on the career dimensions of fre- quency and termination. Maltz explores one approach to disentangling the relationship of inde- pendent covariates to separate career dimensions. To examine the role of covariates on those career dimensions, the data are parti- tioned into groups that are reasonably homogeneous with respect to the covari- ates of interest, end the two dimensions of recidivism are estimated separately for each group.

In an illustrative analysis of the effects of one covariatc age at re- leasc the estimated probability of ever recidivating decreases as age at release increases in three of four jurisdictions examined, but there appears to be no effect of age at release on failure rates for those who do recidivate Maltz, This approach, however, is still preliminary, and considerable develop- ment and testing are required to identify the statistical properties of the technique.

The problem of identifying and control- ling for the effects of independent covariates on the various career dimen- sions remains an important area for fur- ther research development.

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The vari- ous estimation strategies that are applier! The accuracy of the estimates of criminal careers that emerge clepencis on the adequacy of the assump- tions in the models, which are usually unstated. Because the available observable data are only indirect indicators of actual crimes committed, improving the preci- sion of measurement of those data is only one part of needed work; estimates for the underlying, but unobserved, crime proc- ess must also be improved.

This second! With explicit models, the adequacy of estimates can be assesses] in terms of the reasonableness of the as- sumptions ant] the sensitivity of results to those assumptions.

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Models of incliviclual offending have moved from treatments of offending based on traditional aggregate measures such as per capita crime rates and recidi- vism rates to more detailed characteriza- tions that partition offending levels among the various aspects of a criminal career. The initial models of criminal ca- reers have relied on a number of simpli- fying assumptions, principally that indi- vidual careers are stationary over time ant!