Готові списки джерел за темами / Child identification

Добірка наукової літератури з теми "Child identification"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Child identification"

1

Wright, Kirsty, Amy Mundorff, Janet Chaseling, Christopher Maguire, and Denis I. Crane. "Identifying child victims of the South-East Asia Tsunami in Thailand." Disaster Prevention and Management: An International Journal 27, no. 4 (August 6, 2018): 447–55. http://dx.doi.org/10.1108/dpm-02-2018-0044.

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Purpose The purpose of this paper is to reveal difficulties associated with identifying child victims of the 2004 South-East Asia Tsunami at the Thai Tsunami Victim Identification (TTVI) operation in Phuket and explores two strategies that increased child identifications. Design/methodology/approach Data allowing comparison of identification proportions between adult and child (defined as ⩽16 years old) victims of six nationalities and the forensic methods used to establish identification were used in this study. Findings The first 100 days of the operation revealed that the proportion of adult identifications far outweighed the proportion of child identifications. Moreover, the younger the child, the longer the identification process took (p<0.0001). Children under the age of 1 year took an average of 195 days to identify compared to 130 days for children aged 16. Identification was extended, on average, 4.3 days for each year that victims younger were than 16. Identifying large numbers of child victims requires targeted protocols. Two efforts increased child identifications for the TTVI operation: using body length to distinguish post-mortem (PM) DNA samples potentially belonging to children for targeted testing, and singling out deceased parents of missing children who were previously identified by a modality other than DNA, in order to retrieve and test their PM samples as references for kinship matching. Disaster victim identification operations with similar characteristics may benefit from implementing a strategy targeting child identifications. Originality/value The implementation of these two strategies at the TTVI helped to overcome initial complexities, namely, the lack of ante-mortem and PM material, and increased child identifications.
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2

Harlow, Elizabeth. "Child Neglect: Identification and Assessment." Child & Family Social Work 12, no. 4 (November 2007): 440–41. http://dx.doi.org/10.1111/j.1365-2206.2007.00520.x.

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3

ZHOU, PENG, and STEPHEN CRAIN. "Focus identification in child Mandarin." Journal of Child Language 37, no. 5 (November 16, 2009): 965–1005. http://dx.doi.org/10.1017/s0305000909990110.

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ABSTRACTIn this study, we investigated how Mandarin-speaking children and adults interpret focus structures like Zhiyou Yuehan chi-le pingguo ‘Only John ate an apple’ and Shi Yuehan chi-de pingguo ‘It is John who ate an apple’. We found that children tended to associate focus operators zhiyou ‘only’ and shi ‘be’ with the verb phrase (VP), whereas adults uniquely associated them with the subject noun phrase (NP). To account for this difference, we propose that children initially treat focus operators as adverbials, thus ending up associating them with the VP. In order to assess our proposal, we examined children's understanding of zhiyou-constructions with negation, like Zhiyou Yuehan meiyou chi pingguo ‘Only John didn't eat an apple’. It was found that children, like adults, consistently associated the focus operator with the subject NP in this construction. The findings have an important bearing on language learnability, since negation assists children in reaching the adult-like interpretation.
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4

Gafni, Chen. "Child Consonant Harmony: Identification and Properties." Brill's Annual of Afroasiatic Languages and Linguistics 4, no. 1 (January 1, 2012): 30–54. http://dx.doi.org/10.1163/18776930-00400002.

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5

Kiani, Ehsan, Mohamad Al Shahadat, and Fahreddin Sadikoglu. "Child perception-based plant species identification." Procedia Computer Science 120 (2017): 357–64. http://dx.doi.org/10.1016/j.procs.2017.11.250.

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6

Parliament, Lisa, and A. Daniel Yarmey. "Deception in Eyewitness Identification." Criminal Justice and Behavior 29, no. 6 (December 2002): 734–46. http://dx.doi.org/10.1177/009385402237925.

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One-hundred twenty-eight undergraduates were shown a videotape of a staged crime of a young man abducting a child. Participants were instructed to role-play eyewitness behaviors in which they (a) lied to protect the perpetrator; (b) lied to protect the perpetrator but told the truth about the child; (c) lied to ensure the conviction of the perpetrator; or (d) responded truthfully and accurately to the best of their ability. One week later, participants were given a target-present or target-absent photo lineup of both the perpetrator and the child-victim. Participants instructed to lie to protect the perpetrator consistently stated he was not present as opposed to selecting an innocent person. In addition, participants lying to protect the perpetrator were significantly quicker to make identification decisions than participants attempting to make an accurate identification. There were no significant differences between groups in identification performance or in decision times involving the child lineup.
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Kolko, David J., and Alan E. Kazdin. "PARENT-CHILD CORRESPONDENCE IN IDENTIFICATION OF FIRESETTING AMONG CHILD PSYCHIATRIC PATIENTS." Journal of Child Psychology and Psychiatry 29, no. 2 (March 1988): 175–84. http://dx.doi.org/10.1111/j.1469-7610.1988.tb00702.x.

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Alrimawi, Intima, Ahmad Rajeh Saifan, and Mohannad AbuRuz. "Barriers to Child Abuse Identification and Reporting." Journal of Applied Sciences 14, no. 21 (October 15, 2014): 2793–803. http://dx.doi.org/10.3923/jas.2014.2793.2803.

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Fischer, Stephen G. "FBI outreach program promotes child safety, identification." Freedom from Fear 2010, no. 8 (March 12, 2010): 66–67. http://dx.doi.org/10.18356/b87658ff-en.

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Rose, Vera. "Identification and treatment of the dyslipidemic child." Current Opinion in Pediatrics 2, no. 5 (October 1990): 967–72. http://dx.doi.org/10.1097/00008480-199010000-00021.

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Дисертації з теми "Child identification"

1

Pozzulo, Joanna D. "Increasing the identification accuracy of child eyewitnesses with identification procedures." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0004/NQ27850.pdf.

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2

Chaudhry, M. N. "The identification of child neglect in social work practice." Thesis, University of Salford, 2017. http://usir.salford.ac.uk/41619/.

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Statistics highlight child neglect is the most common form of child maltreatment within the United Kingdom. The research described here was an exploratory study which used the pragmatic approach of a survey design to explore how social workers identify child neglect. Social workers complete assessments of children in need of help and protection and this assessment process determines whether a referral should be responded to as a child in need of support (as per Section 17, Children Act 1989) or as a child in need of protection (as per Section 47, Children Act 1989). The definition of child neglect is provided by the Department for Education for use by social workers in its assessment. However, the usefulness of the definition of child neglect is questioned within the literature due to differences in the breath and scope of what is considered a basic need and differences in what are considered to be adequate standards of provision to meet them. The study used an online survey directed at members of the British Association of Social Workers (BASW) and social workers from one Local Authority in the North West of England. There were five sections in the online survey: information on participants’ demographics, the second category focussed on caseloads, identification of child neglect, resources to support the identification of child neglect resources and finally the health and wellbeing of social workers. The major findings were that factors relating to the child were most salient when assessing neglect. This is in clear contrast to previous studies using the same criteria which found that factors relating to the parent were the most significant. The definition of child neglect provided by the Department for Education was highlighted as being problematic with approximately two thirds of participants reporting that the definition was helpful but over a third of participants found it unhelpful. Challenges in defining child neglect appear to be exacerbated by a lack of agreement among professionals from the same group on the nature of neglect. Up to one third of participants reported that they did not feel equipped to work with families in cases of neglect, and approximately half of participants reported that they were not able to follow up on concerns due to their workload. The implication of the findings is that whilst neglect continues to be a primary reason for social work intervention, social work practitioners appear to be working with a definition which the majority find helpful yet acknowledge that there is much less consensus on the nature of neglect. This is a concerning matter as social work practitioners are working with ambiguity yet are agents of the state protecting children from harm when they are unclear about thresholds and level of need.
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3

Clark, Jessica Celeste. "Automated Identification of Adverbial Clauses in Child Language Samples." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd2803.pdf.

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Brown, Brittany Cheree. "Automated Identification of Adverbial Clauses in Child Language Samples." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3404.

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Adverbial clauses are grammatical constructions that are of relevance in both typical language development and impaired language development. In recent years, computer software has been used to assist in the automated analysis of clinical language samples. This software has attempted to accurately identify adverbial clauses with limited success. The present study investigated the accuracy of software for the automated identification of adverbial clauses. Two separate collections of language samples were used. One collection included 10 children with language impairment, with ages ranging from 7;6 to 11;1 (years;months), 10 age-matched peers,and 10 language-matched peers. A second collection contained 30 children ranging from 2;6 to 7;11 in age, with none considered to have language or speech impairments. Language sample utterances were manually coded for the presence of adverbial clauses (both finite and non-finite). Samples were then automatically tagged using the computer software. Results were tabulated and compared for accuracy. ANOVA revealed differences in frequencies of so-adverbial clauses whereas ANACOVA revealed differences in frequencies of both types of finite adverbial clauses. None of the structures were significantly correlated with age; however, frequencies of both types of finite adverbial clauses were correlated with mean length of utterance. Kappa levels revealed that agreement between manual and automated coding was high on both types of finite adverbial clauses.
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Michaelis, Hali Anne. "Automated Identification of Relative Clauses in Child Language Samples." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/1997.

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Анотація:
Previously existing computer analysis programs have been unable to correctly identify many complex syntactic structures thus requiring further manual analysis by the clinician. Complex structures, including the relative clause, are of interest in child language samples due to the difference in development between children with and without language impairment. The purpose of this study was to assess the comparability of results from a new automated program, Cx, to results from manual identification of relative clauses. On language samples from 10 children with language impairment (LI), 10 language matched peers (LA), and 10 chronologically age matched peers (CA), a computerized analysis based on probabilities of sequences of grammatical markers agreed with a manual analysis with a Kappa of 0.88.
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Ehlert, Erika E. "Automated Identification of Relative Clauses in Child Language Samples." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3615.

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Анотація:
Relative clauses are grammatical constructions that are of relevance in both typical and impaired language development. Thus, the accurate identification of these structures in child language samples is clinically important. In recent years, computer software has been used to assist in the automated analysis of clinical language samples. However, this software has had only limited success when attempting to identify relative clauses. The present study explores the development and clinical importance of relative clauses and investigates the accuracy of the software used for automated identification of these structures. Two separate collections of language samples were used. The first collection included 10 children with language impairment, ranging in age from 7;6 to 11;1 (years;months), 10 age-matched peers, and 10 language-matched peers. A second collection contained 30 children considered to have typical speech and language skills and who ranged in age from 2;6 to 7;11. Language samples were manually coded for the presence of relative clauses (including those containing a relative pronoun, those without a relative pronoun and reduced relative clauses). These samples were then tagged using computer software and finally tabulated and compared for accuracy. ANACOVA revealed a significant difference in the frequency of relative clauses containing a relative pronoun but not for those without a relative pronoun nor for reduce relative clauses. None of the structures were significantly correlated with age; however, frequencies of both relative clauses with and without relative pronouns were correlated with mean length of utterance. Kappa levels revealed that agreement between manual and automated coding was relatively high for each relative clause type and highest for relative clauses containing relative pronouns.
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7

Little, Jane Kathryn. "The acquisition of gender stereotype component links." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28105.

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Deaux and Lewis (1984) have proposed that stereotypes be viewed as linked components, each encompassing specific content domains (such as beliefs about appearance, preferences, occupations and traits). Each component has a masculine and a feminine version. Adults are able to use the stereotyped associative links between items in the same component and those between items in different components to make judgments about individuals' behaviors and characteristics based on minimal information. The present study examined the acquisition of these associative connections in the gender stereotypes of 6 to 10 year olds. Seventy-six children (38 boys, 38 girls), aged 6, 8 and 10 years, were asked to make a number of judgments about an individual's clothing, occupational aspirations, toy preferences, and personality traits based on a single piece of cue information (a masculine or feminine item from a component). The types of associative links that children could use in making of interpersonal judgments changed with age. The 6-year-old children were able to make stereotyped judgments about both masculine and feminine items within the same component but were only able to make between-component stereotyped judgments when items of their own-sex typing (i.e. masculine items for boys, feminine items for girls) were presented as cues. The older children were be able to make within- and between-component stereotypic judgments about both masculine and feminine items. The results supported the propositions of schematic-processing theory (Martin & Halverson, 1981) and demonstrated the value of the Deaux and Lewis (1984) component-link model as a heuristic for the study of complex cognitive structures.
Education, Faculty of
Educational and Counselling Psychology, and Special Education (ECPS), Department of
Graduate
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8

Hedengren, Mary L. "National Identity Transnational Identification: The City and the Child as Evidence of Identification Among the Poetic Elite." Diss., CLICK HERE for online access, 2010. http://contentdm.lib.byu.edu/ETD/image/etd3452.pdf.

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9

Stiles, Kathleen Ellis. "Identification of the Adlerian Life Style: Development of an Instrument for Children." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc332676/.

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Alfred Adler's Individual Psychology emphasizes the uniqueness of individuals and describes the life style, or personality, as the unique and characteristic pattern of coping with and solving problems and interacting with other people. The purpose of this study was the development of a similar instrument that would quantitatively identify life styles in children.
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10

Clark, James. "A politics of surfacing, an essay on child abuse, memory, and identification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ57982.pdf.

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Книги з теми "Child identification"

1

Secret child. Basingstoke: Pickering & Inglis, 1986.

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2

Child neglect: Identification and assessment. Basingstoke [England]: Palgrave Macmillan, 2007.

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3

Horwath, Jan. Child Neglect: Identification and Assessment. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4.

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4

A, Blackman James, ed. Identification and assessment in early intervention. Gaithersburg, Md: Aspen Publishers, 1995.

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5

D, Jacobs Linda Ph, and Wachs Carol, eds. Parent-focused child therapy: Attachment, identification, and reflective functions. Lanham, Md: Jason Aronson, 2006.

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6

Tyndall, Filomena M. Parent-child concordance on identification of children's close friends. Ottawa: National Library of Canada, 1994.

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7

Handbook of child sexual abuse: Identification, assessment, and treatment. Hoboken, N.J: John Wiley & Sons, 2012.

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8

Educating the intelligent child. Cambridge: Mensa, 1990.

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9

The emotionally abused and neglected child: Identification, assessment, and intervention. Chichester: Wiley, 1995.

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10

Garbarino, James. The psychologically battered child: (strategies for identification, assessment, and intervention). San Francisco: Jossey-Bass, 1988.

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Частини книг з теми "Child identification"

1

Keren, Miri, Astrid Berg, Palvi Kaukonnen, and Kai von Klitzing. "Early Identification of Psychopathology." In Child and Adolescent Psychiatry, 229–44. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3619-1_13.

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Horwath, Jan. "Introduction." In Child Neglect: Identification and Assessment, 1–9. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_1.

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3

Horwath, Jan. "Working with Child Neglect: Developing Practitioner and Organisational Capacity." In Child Neglect: Identification and Assessment, 209–32. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_10.

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Horwath, Jan. "Defining Child Neglect: The Influence of Time and Place." In Child Neglect: Identification and Assessment, 13–40. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_2.

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Horwath, Jan. "Living with Child Neglect: The Impact on Children." In Child Neglect: Identification and Assessment, 41–68. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_3.

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Horwath, Jan. "Carer Behaviours: The Past Influencing the Present?" In Child Neglect: Identification and Assessment, 71–91. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_4.

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Horwath, Jan. "Parenting Issues and Child Neglect: What Do We Know?" In Child Neglect: Identification and Assessment, 92–111. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_5.

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Horwath, Jan. "The Care-Giving Context." In Child Neglect: Identification and Assessment, 112–26. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_6.

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Horwath, Jan. "Identifying and Referring Cases of Child Neglect: The Theory and the Practice." In Child Neglect: Identification and Assessment, 133–55. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_7.

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Horwath, Jan. "The Assessment Task and Process: Factors that Promote and Inhibit a Child Focus." In Child Neglect: Identification and Assessment, 156–84. London: Macmillan Education UK, 2007. http://dx.doi.org/10.1007/978-0-230-20982-4_8.

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Тези доповідей конференцій з теми "Child identification"

1

Hanani, Abualseoud, Mays Attari, Atta' Farakhna, Aseel Joma'A, Mohammed Hussein, and Stephen Taylor. "Automatic Identification of Articulation Disorders for Arabic Children Speakers." In Workshop on Child Computer Interaction. ISCA, 2016. http://dx.doi.org/10.21437/wocci.2016-6.

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2

Chandran, Pournami S., N. B. Byju, R. U. Deepak, K. N. Nishakumari, P. Devanand, and P. M. Sasi. "Missing Child Identification System Using Deep Learning and Multiclass SVM." In 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS). IEEE, 2018. http://dx.doi.org/10.1109/raics.2018.8635054.

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3

Bansal, Mohan, and Pradip Sircar. "Phoneme Based Model for Gender Identification and Adult-Child Classification." In 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS). IEEE, 2019. http://dx.doi.org/10.1109/icspcs47537.2019.9008704.

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4

Kalli, Revekka, and Miltiades E. Anagnostou. "Re-Identification risk in anonymized data sets with parent-child information." In 2021 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM). IEEE, 2021. http://dx.doi.org/10.1109/seeda-cecnsm53056.2021.9566230.

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5

Chan, Benedict, Shirin Harandi, Daiana Bassi, Sue Conner, Yun Fu, Dean Mohamedally, Gemma Molyneux, Graham Roberts, and Neil Sebire. "75 Computer vision for object detection; machine learning-based identification of surgical equipment." In GOSH Conference 2019, Care of the Complex Child. BMJ Publishing Group Ltd and Royal College of Paediatrics and Child Health, 2019. http://dx.doi.org/10.1136/archdischild-2019-gosh.75.

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Mukherjee, Sumit, Tina Sederholm, Anthony C. Roman, Ria Sankar, Sherrie Caltagirone, and Juan Lavista Ferres. "A machine learning pipeline for aiding school identification from child trafficking images." In GoodIT '21: Conference on Information Technology for Social Good. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3462203.3475924.

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Zavalishina, Olga V., and Rakhym Zhuldyz. "Identification of special educational needs and their assessment in preschool children." In Особый ребенок: Обучение, воспитание, развитие. Yaroslavl state pedagogical university named after К. D. Ushinsky, 2021. http://dx.doi.org/10.20323/978-5-00089-474-3-2021-212-220.

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The article reveals the theoretical foundations and practical procedures for identifying and assessing the special educational needs of preschool children. The content of the article describes a stepby-step procedure for conducting a diagnostic study, the corresponding methodological tools. Attention is focused on the need for acomprehensive analysis of the mechanisms and causes of difficulties in the learning and development of a preschool child.
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Lopez, Angeles. "Finding Evidence Of The Sexual Predators Behavior." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai201912081.

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Sexual predator identification is a critical problem given that the majority of cases of sexually assaulted children have agreed voluntarily to meet with their abuser [10]. Traditionally, a term that is used to describe malicious actions with a potential aim of sexual exploitation or emotional connection with a child is referred to as “Child Grooming” or “Grooming Attack” [6]. This attack is defined by [4] as “a communication process by which a perpetrator applies affinity seeking strategies, while simultaneously engaging in sexual desensitization and information acquisition about targeted victims in order to develop relationships that result in need fulfillment” (e.g. physical sexual molestation). Clearly, the detection of a malicious predatory behavior against a child could reduce the number of abused children.
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Gosztolya, Gábor, Róbert Busa-Fekete, Tamás Grósz, and László Tóth. "DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification." In Interspeech 2017. ISCA: ISCA, 2017. http://dx.doi.org/10.21437/interspeech.2017-905.

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10

Dongxin Xu, J. Gilkerson, and J. A. Richards. "Objective child behavior measurement with naturalistic daylong audio recording and its application to autism identification." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6346772.

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Звіти організацій з теми "Child identification"

1

Agostinelli, Francesco, and Matthew Wiswall. Identification of Dynamic Latent Factor Models: The Implications of Re-Normalization in a Model of Child Development. Cambridge, MA: National Bureau of Economic Research, July 2016. http://dx.doi.org/10.3386/w22441.

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2

Melnyk, Maryna. Research of awareness and attitude of the pedagogical community, students and parents to the diagnosis and support of gifted personality development. Institute of Gifted Children of the National Academy of Educational Sciences of Ukraine, 2021. http://dx.doi.org/10.32405/iodnapn-zvit-2021-52.

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Анотація:
The paper presents the results of the survey among the pedagogical community, students and parents on awareness and attitude to the identification and support of gifted personality, conducted by the Institute of Gifted Child of NAES of Ukraine in the period from 03.09 to 30.09.2021.
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3

Parker, Michael, Alex Stott, Brian Quinn, Bruce Elder, Tate Meehan, and Sally Shoop. Joint Chilean and US mobility testing in extreme environments. Engineer Research and Development Center (U.S.), November 2021. http://dx.doi.org/10.21079/11681/42362.

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Vehicle mobility in cold and challenging terrains is of interest to both the US and Chilean Armies. Mobility in winter conditions is highly vehicle dependent with autonomous vehicles experiencing additional challenges over manned vehicles. They lack the ability to make informed decisions based on what they are “seeing” and instead need to rely on input from sensors on the vehicle, or from Unmanned Aerial Systems (UAS) or satellite data collections. This work focuses on onboard vehicle Controller Area Network (CAN) Bus sensors, driver input sensors, and some externally mounted sensors to assist with terrain identification and overall vehicle mobility. Analysis of winter vehicle/sensor data collected in collaboration with the Chilean Army in Lonquimay, Chile during July and August 2019 will be discussed in this report.
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4

Altamirano Montoya, Álvaro, Mariano Bosch, Carolina Cabrita Felix, Rodrigo Cerda, Manuel García-Huitrón, Laura Karina Gutiérrez, and Waldo Tapia Troncoso. 2020 Pension Indicators for Latin America and the Caribbean. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002967.

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The PLAC Network's Pension Indicators are a dataset containing information related to the labor markets and pension systems of the nineteen PLAC Network member countries: Argentina, Bahamas, Barbados, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, El Salvador, Guyana, Haiti, Honduras, Jamaica, Mexico, Panama, Paraguay, Peru, Trinidad and Tobago, and Uruguay. The indicators are divided into five main categories: environment, performance, sustainability, society's preparedness for aging and reform, and pension system design. Each one of these categories are divided into a few subcategories as well. These indicators were constructed with the objective of becoming an important tool for the improvement of the following aspects of pension systems: coverage, sufficiency of benefits, financial sustainability, equity and social solidarity, efficiency, and institutional capacity. An important characteristic of this dataset is the comparability of these indicators since it permits the identification of areas of cooperation and knowledge exchange among countries. The dataset is accompanied by a User's Manual, which can be found in this link https://publications.iadb.org/en/users-manual-idb-plac-network-pension-indicators
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5

Altamirano Montoya, Álvaro, Mariano Bosch, Carolina Cabrita Felix, Rodrigo Cerda, Manuel García-Huitrón, Laura Karina Gutiérrez, and Waldo Tapia Troncoso. 2019 Pension Indicators for Latin America and the Caribbean. Inter-American Development Bank, December 2020. http://dx.doi.org/10.18235/0002966.

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Анотація:
The 2019 PLAC Network's Pension Indicators are a dataset containing information related to the labor markets and pension systems of the nineteen PLAC Network member countries: Argentina, Bahamas, Barbados, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, El Salvador, Guyana, Haiti, Honduras, Jamaica, Mexico, Panama, Paraguay, Peru, Trinidad and Tobago, and Uruguay. The indicators are divided into five main categories: environment, performance, sustainability, society's preparedness for aging and reform, and pension system design. Each one of these categories are divided into a few subcategories as well. These indicators were constructed with the objective of becoming an important tool for the improvement of the following aspects of pension systems: coverage, sufficiency of benefits, financial sustainability, equity and social solidarity, efficiency, and institutional capacity. An important characteristic of this dataset is the comparability of these indicators since it permits the identification of areas of cooperation and knowledge exchange among countries. The dataset is accompanied by a User's Manual, which can be found in this link: https://publications.iadb.org/en/users-manual-idb-plac-network-pension-indicators
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6

Banerjee, Onil, Martin Cicowiez, Ana Rios, and Cicero De Lima. Climate Change Impacts on Agriculture in Latin America and the Caribbean: An Application of the Integrated Economic-Environmental Modeling (IEEM) Platform. Inter-American Development Bank, November 2021. http://dx.doi.org/10.18235/0003794.

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In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affected according to key indicators including Gross Domestic Product (GDP), international commerce, sectoral output, poverty, and emissions. Most countries experience negative impacts on GDP, with the exception of the major soybean producing countries, namely, Brazil, Argentina and Uruguay. We find that CC-induced crop productivity and labor productivity changes affect countries differently. The combined impact, however, indicates that Belize, Nicaragua, Guatemala and Paraguay would fare the worst. Early identification of these hardest hit countries can enable policy makers pre-empting these effects and beginning the design of adaptation strategies early on. In terms of greenhouse gas emissions, only Argentina, Chile and Uruguay would experience small increases in emissions.
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